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Dockerfile

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+# Use Python 3.11 image
+FROM python:3.11-slim
+
+WORKDIR /app
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+RUN mkdir -p /app/storage/contexts /app/storage/students /app/storage/progress/assessments /app/storage/progress/skills \
+    && chmod -R 777 /app/storage
+
+RUN mkdir -p /app/static \
+    && cp -r /app/src/static/* /app/static/ 2>/dev/null || true \
+    && chmod -R 755 /app/static
+
+ENV PORT=7860
+ENV PYTHONPATH=/app
+
+EXPOSE 7860
+
+CMD ["python", "main.py"]

README.md

@@ -1,10 +1,25 @@
----
-title: MCP EdTech
-emoji: 👁
-colorFrom: gray
-colorTo: pink
-sdk: docker
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: MCP EdTech Project
+emoji: 🎓
+colorFrom: blue
+colorTo: indigo
+sdk: docker
+sdk_version: "latest"
+app_file: main.py
+pinned: false
+---
+
+# MCP EdTech Project
+
+A comprehensive implementation of the Model Context Protocol (MCP) for educational technology applications.
+
+## Overview
+
+The Model Context Protocol (MCP) is a standardized interface for AI model interactions that allows for consistent handling of context across different models, stateful conversations, and structured input/output formats. This project implements MCP specifically for EdTech applications, providing features such as:
+
+- Context management for stateful conversations
+- Student profile management
+- Learning progress tracking
+- Educational content adaptation
+- Assessment and feedback systems
+- Personalized learning path generation

main.py

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+import os
+import uvicorn
+from fastapi import FastAPI
+from fastapi.staticfiles import StaticFiles
+from fastapi.responses import RedirectResponse, HTMLResponse, JSONResponse
+from fastapi.openapi.docs import get_swagger_ui_html, get_redoc_html
+from fastapi.openapi.utils import get_openapi
+
+from src.api.app import app as api_app
+
+app = FastAPI(title="MCP EdTech", description="Model Context Protocol for Educational Technology")
+
+app.mount("/static", StaticFiles(directory="static"), name="static")
+
+@app.get("/", response_class=HTMLResponse)
+async def serve_root():
+    try:
+        with open("static/index.html", "r") as f:
+            html_content = f.read()
+        return HTMLResponse(content=html_content)
+    except Exception as e:
+        return JSONResponse(content={
+            "name": "MCP EdTech API",
+            "version": "1.0.0",
+            "description": "Model Context Protocol implementation for EdTech applications",
+            "demo_ui": "Please visit /demo for the interactive demo"
+        })
+
+@app.get("/demo", response_class=HTMLResponse)
+async def serve_demo():
+    with open("static/index.html", "r") as f:
+        html_content = f.read()
+    return HTMLResponse(content=html_content)
+
+for route in api_app.routes:
+    app.routes.append(route)
+
+def custom_openapi():
+    if app.openapi_schema:
+        return app.openapi_schema
+    openapi_schema = get_openapi(
+        title="MCP EdTech API BY MHA",
+        version="1.0.0",
+        description="Model Context Protocol implementation for EdTech applications",
+        routes=app.routes,
+    )
+    app.openapi_schema = openapi_schema
+    return app.openapi_schema
+
+app.openapi = custom_openapi
+
+if __name__ == "__main__":
+    port = int(os.environ.get("PORT", 7860))
+    uvicorn.run(app, host="0.0.0.0", port=port)

project_plan.md

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+# MCP EdTech Project Plan
+
+## Project Overview
+This project implements the Model Context Protocol (MCP) for educational technology applications. The implementation will provide a standardized way for EdTech applications to interact with various AI models while maintaining context and state across interactions.
+
+## What is Model Context Protocol (MCP)?
+The Model Context Protocol (MCP) is a standardized interface for AI model interactions that allows for:
+- Consistent handling of context across different models
+- Stateful conversations and interactions
+- Structured input/output formats
+- Model-agnostic implementations
+- Enhanced security and privacy controls
+
+## Project Architecture
+
+### Core Components
+1. **MCP Core**
+   - Protocol specification implementation
+   - Context management system
+   - State persistence layer
+   - Model interface adapters
+
+2. **EdTech-Specific Extensions**
+   - Student profile management
+   - Learning progress tracking
+   - Educational content adaptation
+   - Assessment and feedback systems
+
+3. **API Layer**
+   - RESTful endpoints
+   - WebSocket support for real-time interactions
+   - Authentication and authorization
+   - Rate limiting and usage monitoring
+
+4. **Demo Applications**
+   - Interactive tutoring system
+   - Personalized learning path generator
+   - Knowledge assessment tool
+
+## Technical Stack
+- **Backend**: FastAPI
+- **Database**: SQLite (development), PostgreSQL (production)
+- **Authentication**: JWT-based auth
+- **Documentation**: OpenAPI/Swagger, ReDoc
+- **Testing**: Pytest
+- **Deployment**: Docker, Hugging Face Spaces, Heroku/Render compatibility
+
+## Implementation Plan
+
+### Phase 1: Core MCP Implementation
+- Define MCP specification for EdTech use cases
+- Implement context management system
+- Create model interface adapters
+- Develop state persistence layer
+
+### Phase 2: EdTech Extensions
+- Implement student profile management
+- Create learning progress tracking
+- Develop educational content adaptation
+- Build assessment and feedback systems
+
+### Phase 3: API Development
+- Design and implement RESTful endpoints
+- Add WebSocket support
+- Implement authentication and authorization
+- Add rate limiting and usage monitoring
+
+### Phase 4: Demo Applications
+- Build interactive tutoring system
+- Create personalized learning path generator
+- Develop knowledge assessment tool
+
+### Phase 5: Documentation and Deployment
+- Write comprehensive documentation
+- Create usage examples
+- Prepare deployment configurations
+- Deploy to Hugging Face and prepare for Heroku/Render
+
+## API Endpoints
+
+### MCP Core Endpoints
+- `POST /api/v1/context/create` - Create a new context
+- `GET /api/v1/context/{context_id}` - Get context information
+- `PUT /api/v1/context/{context_id}` - Update context
+- `DELETE /api/v1/context/{context_id}` - Delete context
+- `POST /api/v1/interact` - Process an interaction within a context
+
+### EdTech-Specific Endpoints
+- `POST /api/v1/students` - Create student profile
+- `GET /api/v1/students/{student_id}` - Get student information
+- `PUT /api/v1/students/{student_id}` - Update student information
+- `GET /api/v1/students/{student_id}/progress` - Get learning progress
+- `POST /api/v1/assessments` - Create assessment
+- `GET /api/v1/learning-paths/{student_id}` - Get personalized learning path
+
+## Deployment Strategy
+1. **Development Environment**
+   - Local development with SQLite
+   - Docker containerization for consistent environments
+
+2. **Testing Environment**
+   - Automated testing with GitHub Actions
+   - Integration testing with test databases
+
+3. **Production Deployment**
+   - Hugging Face Spaces for showcase
+   - Deployment scripts for Heroku and Render
+   - PostgreSQL for production database
+
+## Documentation Plan
+1. **Technical Documentation**
+   - MCP specification
+   - API reference
+   - Architecture overview
+   - Database schema
+
+2. **User Documentation**
+   - Getting started guide
+   - Integration examples
+   - Deployment instructions
+   - Customization guide
+
+3. **Demo Documentation**
+   - Use case examples
+   - Interactive tutorials
+   - Sample applications
+
+## Timeline
+- Phase 1: 1-2 weeks
+- Phase 2: 1-2 weeks
+- Phase 3: 1 week
+- Phase 4: 1-2 weeks
+- Phase 5: 1 week
+
+Total estimated time: 5-8 weeks for full implementation

requirements.txt

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+fastapi>=0.95.0
+uvicorn>=0.21.0
+pydantic>=2.0.0
+sqlalchemy>=2.0.0
+python-jose[cryptography]>=3.3.0
+passlib[bcrypt]>=1.7.4
+python-multipart>=0.0.6
+pytest>=7.3.1
+httpx>=0.24.0
+aiosqlite>=0.19.0
+websockets>=11.0.3

src/api/app.py

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+"""
+API Layer - FastAPI Application
+
+This module implements the FastAPI application for the MCP EdTech project,
+providing RESTful endpoints for interacting with the MCP system.
+"""
+
+import os
+from typing import Dict, List, Optional, Any, Union
+from datetime import datetime, timedelta
+
+from fastapi import FastAPI, Depends, HTTPException, status, BackgroundTasks
+from fastapi.security import OAuth2PasswordBearer, OAuth2PasswordRequestForm
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import JSONResponse, FileResponse
+from fastapi.staticfiles import StaticFiles
+from pydantic import BaseModel
+
+from ..mcp_core.context import Context, ContextManager
+from ..mcp_core.model_adapters import ModelRegistry, MockModelAdapter
+from ..mcp_core.processor import InteractionProcessor
+from ..mcp_core.protocol import (
+    MCPRequest, MCPResponse, InteractionType, ContentFormat,
+    EducationalLevel, LearningObjective, StudentProfile
+)
+from ..edtech_extensions.student_profile import StudentProfileManager
+from ..edtech_extensions.progress_tracking import ProgressTracker, AssessmentType
+from ..edtech_extensions.content_adaptation import ContentAdapter
+
+
+# Initialize FastAPI app
+app = FastAPI(
+    title="MCP EdTech API",
+    description="Model Context Protocol implementation for EdTech applications",
+    version="1.0.0"
+)
+
+# Add CORS middleware
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # In production, specify actual origins
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# Initialize core components
+context_manager = ContextManager()
+model_registry = ModelRegistry()
+
+# Register mock model adapter for demonstration
+mock_adapter = MockModelAdapter(model_id="mock-edtech-model")
+model_registry.register_adapter("mock", mock_adapter)
+
+# Initialize processor
+interaction_processor = InteractionProcessor(context_manager, model_registry)
+
+# Initialize EdTech extensions
+os.makedirs("./storage", exist_ok=True)
+student_profile_manager = StudentProfileManager()
+progress_tracker = ProgressTracker()
+content_adapter = ContentAdapter()
+
+
+# API Models
+
+class ContextCreate(BaseModel):
+    """Request model for creating a new context."""
+    metadata: Dict[str, Any] = {}
+
+
+class ContextUpdate(BaseModel):
+    """Request model for updating a context."""
+    metadata: Dict[str, Any] = {}
+    state: Dict[str, Any] = {}
+
+
+class InteractionRequest(BaseModel):
+    """Request model for processing an interaction."""
+    context_id: Optional[str] = None
+    interaction_type: InteractionType
+    content: Dict[str, Any]
+    format: ContentFormat = ContentFormat.TEXT
+    metadata: Dict[str, Any] = {}
+    model_name: str = "mock"  # Default to mock model
+
+
+class StudentProfileCreate(BaseModel):
+    """Request model for creating a student profile."""
+    name: str
+    educational_level: EducationalLevel
+    learning_style: Optional[str] = None
+    interests: List[str] = []
+    strengths: List[str] = []
+    areas_for_improvement: List[str] = []
+
+
+class StudentProfileUpdate(BaseModel):
+    """Request model for updating a student profile."""
+    name: Optional[str] = None
+    educational_level: Optional[EducationalLevel] = None
+    learning_style: Optional[str] = None
+    interests: Optional[List[str]] = None
+    strengths: Optional[List[str]] = None
+    areas_for_improvement: Optional[List[str]] = None
+
+
+class AssessmentCreate(BaseModel):
+    """Request model for creating an assessment."""
+    student_id: str
+    assessment_type: AssessmentType
+    title: str
+    score: float
+    max_score: float
+    objectives: List[str]
+    feedback: str = ""
+    details: Dict[str, Any] = {}
+
+
+class ContentAdaptRequest(BaseModel):
+    """Request model for adapting content."""
+    content: Dict[str, Any]
+    student_id: str
+    learning_objectives: List[str]
+    content_format: ContentFormat = ContentFormat.TEXT
+
+
+# API Routes
+
+@app.get("/")
+async def root():
+    """Root endpoint returning API information."""
+    return {
+        "name": "MCP EdTech API",
+        "version": "1.0.0",
+        "description": "Model Context Protocol implementation for EdTech applications"
+    }
+
+
+# Context endpoints
+
+@app.post("/api/v1/context/create", response_model=Dict[str, Any])
+async def create_context(request: ContextCreate):
+    """Create a new context."""
+    context = context_manager.create_context(metadata=request.metadata)
+    return context.to_dict()
+
+
+@app.get("/api/v1/context/{context_id}", response_model=Dict[str, Any])
+async def get_context(context_id: str):
+    """Get context information."""
+    context = context_manager.get_context(context_id)
+    if not context:
+        raise HTTPException(status_code=404, detail="Context not found")
+    return context.to_dict()
+
+
+@app.put("/api/v1/context/{context_id}", response_model=Dict[str, Any])
+async def update_context(context_id: str, request: ContextUpdate):
+    """Update context."""
+    context = context_manager.get_context(context_id)
+    if not context:
+        raise HTTPException(status_code=404, detail="Context not found")
+        
+    if request.metadata:
+        context.metadata.update(request.metadata)
+        
+    if request.state:
+        context.update_state(request.state)
+        
+    return context.to_dict()
+
+
+@app.delete("/api/v1/context/{context_id}", response_model=Dict[str, str])
+async def delete_context(context_id: str):
+    """Delete context."""
+    success = context_manager.delete_context(context_id)
+    if not success:
+        raise HTTPException(status_code=404, detail="Context not found")
+    return {"status": "deleted", "context_id": context_id}
+
+
+# Interaction endpoint
+
+@app.post("/api/v1/interact", response_model=Dict[str, Any])
+async def process_interaction(request: InteractionRequest):
+    """Process an interaction."""
+    try:
+        mcp_request = MCPRequest(
+            context_id=request.context_id,
+            interaction_type=request.interaction_type,
+            content=request.content,
+            format=request.format,
+            metadata=request.metadata
+        )
+        
+        response = await interaction_processor.process_interaction(
+            mcp_request,
+            request.model_name
+        )
+        
+        return response.dict()
+    except ValueError as e:
+        raise HTTPException(status_code=400, detail=str(e))
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Error processing interaction: {str(e)}")
+
+
+# Student profile endpoints
+
+@app.post("/api/v1/students", response_model=Dict[str, Any])
+async def create_student_profile(request: StudentProfileCreate):
+    """Create student profile."""
+    profile = await student_profile_manager.create_profile(
+        name=request.name,
+        educational_level=request.educational_level,
+        learning_style=request.learning_style,
+        interests=request.interests,
+        strengths=request.strengths,
+        areas_for_improvement=request.areas_for_improvement
+    )
+    return profile.dict()
+
+
+@app.get("/api/v1/students/{student_id}", response_model=Dict[str, Any])
+async def get_student_profile(student_id: str):
+    """Get student information."""
+    profile = await student_profile_manager.get_profile(student_id)
+    if not profile:
+        raise HTTPException(status_code=404, detail="Student profile not found")
+    return profile.dict()
+
+
+@app.put("/api/v1/students/{student_id}", response_model=Dict[str, Any])
+async def update_student_profile(student_id: str, request: StudentProfileUpdate):
+    """Update student information."""
+    updates = {k: v for k, v in request.dict().items() if v is not None}
+    profile = await student_profile_manager.update_profile(student_id, updates)
+    if not profile:
+        raise HTTPException(status_code=404, detail="Student profile not found")
+    return profile.dict()
+
+
+# Progress tracking endpoints
+
+@app.get("/api/v1/students/{student_id}/progress", response_model=Dict[str, Any])
+async def get_student_progress(student_id: str):
+    """Get learning progress."""
+    # Check if student exists
+    profile = await student_profile_manager.get_profile(student_id)
+    if not profile:
+        raise HTTPException(status_code=404, detail="Student profile not found")
+        
+    summary = await progress_tracker.get_progress_summary(student_id)
+    return summary
+
+
+@app.post("/api/v1/assessments", response_model=Dict[str, Any])
+async def create_assessment(request: AssessmentCreate):
+    """Create assessment."""
+    # Check if student exists
+    profile = await student_profile_manager.get_profile(request.student_id)
+    if not profile:
+        raise HTTPException(status_code=404, detail="Student profile not found")
+        
+    result = await progress_tracker.record_assessment(
+        student_id=request.student_id,
+        assessment_type=request.assessment_type,
+        title=request.title,
+        score=request.score,
+        max_score=request.max_score,
+        objectives=request.objectives,
+        feedback=request.feedback,
+        details=request.details
+    )
+    
+    # Update student profile with completed objectives if score is good
+    if request.score / request.max_score >= 0.7:  # 70% or better
+        for objective_id in request.objectives:
+            await student_profile_manager.add_completed_objective(
+                request.student_id,
+                objective_id
+            )
+    
+    return result.dict()
+
+
+@app.get("/api/v1/students/{student_id}/assessments", response_model=List[Dict[str, Any]])
+async def list_student_assessments(student_id: str):
+    """List assessments for a student."""
+    # Check if student exists
+    profile = await student_profile_manager.get_profile(student_id)
+    if not profile:
+        raise HTTPException(status_code=404, detail="Student profile not found")
+        
+    results = await progress_tracker.list_assessments(student_id)
+    return [result.dict() for result in results]
+
+
+# Content adaptation endpoint
+
+@app.post("/api/v1/content/adapt", response_model=Dict[str, Any])
+async def adapt_content(request: ContentAdaptRequest):
+    """Adapt content for a student."""
+    # Get student profile
+    profile = await student_profile_manager.get_profile(request.student_id)
+    if not profile:
+        raise HTTPException(status_code=404, detail="Student profile not found")
+        
+    # Create learning objectives (in a real app, these would come from a database)
+    learning_objectives = [
+        LearningObjective(
+            id=obj_id,
+            description=f"Learning objective {obj_id}",
+            taxonomy_level="understand",
+            subject_area="general",
+            prerequisites=[]
+        )
+        for obj_id in request.learning_objectives
+    ]
+    
+    # Adapt content
+    adapted_content = await content_adapter.adapt_content(
+        content=request.content,
+        student_profile=profile,
+        learning_objectives=learning_objectives,
+        content_format=request.content_format
+    )
+    
+    return adapted_content
+
+
+# Learning path endpoint
+
+@app.get("/api/v1/learning-paths/{student_id}", response_model=Dict[str, Any])
+async def get_learning_path(student_id: str):
+    """Get personalized learning path."""
+    # Check if student exists
+    profile = await student_profile_manager.get_profile(student_id)
+    if not profile:
+        raise HTTPException(status_code=404, detail="Student profile not found")
+        
+    # In a real implementation, this would generate a personalized learning path
+    # based on the student's profile, progress, and available learning materials.
+    # For this demo, we'll return a mock learning path.
+    
+    # Get student's completed objectives
+    completed_objectives = profile.completed_objectives
+    current_objectives = profile.current_objectives
+    
+    # Mock learning path
+    return {
+        "student_id": student_id,
+        "student_name": profile.name,
+        "educational_level": profile.educational_level,
+        "completed_objectives": completed_objectives,
+        "current_objectives": current_objectives,
+        "recommended_objectives": [
+            {
+                "id": f"obj-{i}",
+                "title": f"Recommended Objective {i}",
+                "description": f"This is a recommended learning objective for {profile.name}",
+                "estimated_time": f"{i*2} hours",
+                "difficulty": "intermediate"
+            }
+            for i in range(1, 4)
+        ],
+        "recommended_resources": [
+            {
+                "id": f"res-{i}",
+                "title": f"Resource {i}",
+                "type": "video" if i % 2 == 0 else "article",
+                "url": f"https://example.com/resource-{i}",
+                "description": f"This is a recommended resource for {profile.name}"
+            }
+            for i in range(1, 6)
+        ],
+        "generated_at": datetime.utcnow().isoformat()
+    }
+
+
+# Model information endpoints
+
+@app.get("/api/v1/models", response_model=List[str])
+async def list_models():
+    """List available models."""
+    return model_registry.list_adapters()
+
+
+@app.get("/api/v1/models/{model_name}/capabilities", response_model=Dict[str, Any])
+async def get_model_capabilities(model_name: str):
+    """Get model capabilities."""
+    capabilities = model_registry.get_adapter_capabilities(model_name)
+    if not capabilities:
+        raise HTTPException(status_code=404, detail="Model not found")
+    return capabilities
+
+
+# Health check endpoint
+
+@app.get("/health", response_model=Dict[str, str])
+async def health_check():
+    """Health check endpoint."""
+    return {
+        "status": "healthy",
+        "timestamp": datetime.utcnow().isoformat()
+    }
+
+
+# Demo UI route
+@app.get("/demo", response_class=FileResponse)
+async def demo_ui():
+    """Serve the demo UI."""
+    return FileResponse("static/index.html")
+
+
+# Serve static files for demo UI
+app.mount("/static", StaticFiles(directory="static"), name="static")
+
+
+# Main function to run the app
+def start():
+    """Start the FastAPI application using uvicorn."""
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8000)
+
+
+if __name__ == "__main__":
+    start()

src/demo_apps/demo_ui.py

@@ -0,0 +1,504 @@
+"""
+Demo application for the MCP EdTech project.
+
+This module provides a simple web interface for demonstrating the MCP EdTech functionality.
+"""
+
+import os
+from pathlib import Path
+
+# Create static directory for demo UI
+static_dir = Path(__file__).parent.parent / "static"
+static_dir.mkdir(exist_ok=True)
+
+# Create index.html for the demo UI
+index_html = """<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>MCP EdTech Demo</title>
+    <link href="https://cdn.jsdelivr.net/npm/bootstrap@5.3.0-alpha1/dist/css/bootstrap.min.css" rel="stylesheet">
+    <style>
+        body {
+            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+            padding-top: 20px;
+            background-color: #f8f9fa;
+        }
+        .navbar {
+            background-color: #4a6fa5 !important;
+            box-shadow: 0 2px 4px rgba(0,0,0,0.1);
+        }
+        .navbar-brand {
+            font-weight: bold;
+            color: white !important;
+        }
+        .nav-link {
+            color: rgba(255,255,255,0.85) !important;
+        }
+        .nav-link:hover {
+            color: white !important;
+        }
+        .card {
+            border-radius: 10px;
+            box-shadow: 0 4px 6px rgba(0,0,0,0.1);
+            margin-bottom: 20px;
+            transition: transform 0.3s;
+        }
+        .card:hover {
+            transform: translateY(-5px);
+        }
+        .card-header {
+            background-color: #4a6fa5;
+            color: white;
+            font-weight: bold;
+            border-radius: 10px 10px 0 0 !important;
+        }
+        .btn-primary {
+            background-color: #4a6fa5;
+            border-color: #4a6fa5;
+        }
+        .btn-primary:hover {
+            background-color: #3a5a8f;
+            border-color: #3a5a8f;
+        }
+        .api-url {
+            font-family: monospace;
+            background-color: #f1f1f1;
+            padding: 5px;
+            border-radius: 4px;
+        }
+        .response-area {
+            background-color: #f8f9fa;
+            border: 1px solid #dee2e6;
+            border-radius: 5px;
+            padding: 15px;
+            max-height: 300px;
+            overflow-y: auto;
+            font-family: monospace;
+        }
+        .footer {
+            margin-top: 50px;
+            padding: 20px 0;
+            background-color: #343a40;
+            color: white;
+        }
+        #loading {
+            display: none;
+        }
+        .spinner-border {
+            width: 1rem;
+            height: 1rem;
+        }
+    </style>
+</head>
+<body>
+    <nav class="navbar navbar-expand-lg navbar-dark bg-dark mb-4">
+        <div class="container">
+            <a class="navbar-brand" href="#">MCP EdTech</a>
+            <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbarNav">
+                <span class="navbar-toggler-icon"></span>
+            </button>
+            <div class="collapse navbar-collapse" id="navbarNav">
+                <ul class="navbar-nav">
+                    <li class="nav-item">
+                        <a class="nav-link active" href="#home">Home</a>
+                    </li>
+                    <li class="nav-item">
+                        <a class="nav-link" href="#api-demo">API Demo</a>
+                    </li>
+                    <li class="nav-item">
+                        <a class="nav-link" href="#documentation">Documentation</a>
+                    </li>
+                </ul>
+            </div>
+        </div>
+    </nav>
+
+    <div class="container" id="home">
+        <div class="row mb-4">
+            <div class="col-12">
+                <div class="card">
+                    <div class="card-header">
+                        Model Context Protocol (MCP) for EdTech
+                    </div>
+                    <div class="card-body">
+                        <h5 class="card-title">Welcome to the MCP EdTech Demo</h5>
+                        <p class="card-text">
+                            This demo showcases the Model Context Protocol (MCP) implementation for educational technology applications.
+                            MCP provides a standardized way for EdTech applications to interact with various AI models while maintaining
+                            context and state across interactions.
+                        </p>
+                        <p>
+                            Key features of this implementation:
+                        </p>
+                        <ul>
+                            <li>Context management for stateful conversations</li>
+                            <li>Student profile management</li>
+                            <li>Learning progress tracking</li>
+                            <li>Content adaptation based on student profiles</li>
+                            <li>Assessment and feedback systems</li>
+                        </ul>
+                    </div>
+                </div>
+            </div>
+        </div>
+
+        <div class="row mb-4" id="api-demo">
+            <div class="col-12">
+                <div class="card">
+                    <div class="card-header">
+                        API Demo
+                    </div>
+                    <div class="card-body">
+                        <h5 class="card-title">Try the MCP API</h5>
+                        
+                        <div class="mb-4">
+                            <h6>1. Create a Context</h6>
+                            <p>First, let's create a new context for our interaction:</p>
+                            <div class="mb-3">
+                                <button id="createContextBtn" class="btn btn-primary">Create Context</button>
+                                <span id="loading-context" class="ms-2" style="display: none;">
+                                    <span class="spinner-border spinner-border-sm"></span> Processing...
+                                </span>
+                            </div>
+                            <div class="response-area" id="contextResponse">
+                                <!-- Context response will appear here -->
+                            </div>
+                        </div>
+                        
+                        <div class="mb-4">
+                            <h6>2. Process an Interaction</h6>
+                            <p>Now, let's process an interaction using the context we created:</p>
+                            <div class="mb-3">
+                                <label for="interactionText" class="form-label">Enter your question or prompt:</label>
+                                <input type="text" class="form-control" id="interactionText" 
+                                    placeholder="e.g., Explain the concept of photosynthesis">
+                            </div>
+                            <div class="mb-3">
+                                <button id="interactBtn" class="btn btn-primary">Process Interaction</button>
+                                <span id="loading-interaction" class="ms-2" style="display: none;">
+                                    <span class="spinner-border spinner-border-sm"></span> Processing...
+                                </span>
+                            </div>
+                            <div class="response-area" id="interactionResponse">
+                                <!-- Interaction response will appear here -->
+                            </div>
+                        </div>
+                        
+                        <div class="mb-4">
+                            <h6>3. Create a Student Profile</h6>
+                            <p>Let's create a student profile:</p>
+                            <div class="mb-3">
+                                <label for="studentName" class="form-label">Student Name:</label>
+                                <input type="text" class="form-control" id="studentName" placeholder="John Doe">
+                            </div>
+                            <div class="mb-3">
+                                <label for="educationalLevel" class="form-label">Educational Level:</label>
+                                <select class="form-select" id="educationalLevel">
+                                    <option value="elementary">Elementary</option>
+                                    <option value="middle_school">Middle School</option>
+                                    <option value="high_school">High School</option>
+                                    <option value="undergraduate">Undergraduate</option>
+                                    <option value="graduate">Graduate</option>
+                                    <option value="professional">Professional</option>
+                                </select>
+                            </div>
+                            <div class="mb-3">
+                                <button id="createStudentBtn" class="btn btn-primary">Create Student Profile</button>
+                                <span id="loading-student" class="ms-2" style="display: none;">
+                                    <span class="spinner-border spinner-border-sm"></span> Processing...
+                                </span>
+                            </div>
+                            <div class="response-area" id="studentResponse">
+                                <!-- Student profile response will appear here -->
+                            </div>
+                        </div>
+                        
+                        <div class="mb-4">
+                            <h6>4. Adapt Content for Student</h6>
+                            <p>Now, let's adapt some content for the student:</p>
+                            <div class="mb-3">
+                                <label for="contentText" class="form-label">Content to adapt:</label>
+                                <textarea class="form-control" id="contentText" rows="3" 
+                                    placeholder="The process of photosynthesis involves the conversion of light energy into chemical energy that can be used by plants and other organisms."></textarea>
+                            </div>
+                            <div class="mb-3">
+                                <button id="adaptContentBtn" class="btn btn-primary">Adapt Content</button>
+                                <span id="loading-content" class="ms-2" style="display: none;">
+                                    <span class="spinner-border spinner-border-sm"></span> Processing...
+                                </span>
+                            </div>
+                            <div class="response-area" id="contentResponse">
+                                <!-- Content adaptation response will appear here -->
+                            </div>
+                        </div>
+                    </div>
+                </div>
+            </div>
+        </div>
+
+        <div class="row mb-4" id="documentation">
+            <div class="col-12">
+                <div class="card">
+                    <div class="card-header">
+                        API Documentation
+                    </div>
+                    <div class="card-body">
+                        <h5 class="card-title">Available Endpoints</h5>
+                        
+                        <div class="mb-3">
+                            <h6>Context Management</h6>
+                            <ul>
+                                <li><span class="api-url">POST /api/v1/context/create</span> - Create a new context</li>
+                                <li><span class="api-url">GET /api/v1/context/{context_id}</span> - Get context information</li>
+                                <li><span class="api-url">PUT /api/v1/context/{context_id}</span> - Update context</li>
+                                <li><span class="api-url">DELETE /api/v1/context/{context_id}</span> - Delete context</li>
+                            </ul>
+                        </div>
+                        
+                        <div class="mb-3">
+                            <h6>Interaction</h6>
+                            <ul>
+                                <li><span class="api-url">POST /api/v1/interact</span> - Process an interaction</li>
+                            </ul>
+                        </div>
+                        
+                        <div class="mb-3">
+                            <h6>Student Profiles</h6>
+                            <ul>
+                                <li><span class="api-url">POST /api/v1/students</span> - Create student profile</li>
+                                <li><span class="api-url">GET /api/v1/students/{student_id}</span> - Get student information</li>
+                                <li><span class="api-url">PUT /api/v1/students/{student_id}</span> - Update student information</li>
+                            </ul>
+                        </div>
+                        
+                        <div class="mb-3">
+                            <h6>Progress Tracking</h6>
+                            <ul>
+                                <li><span class="api-url">GET /api/v1/students/{student_id}/progress</span> - Get learning progress</li>
+                                <li><span class="api-url">POST /api/v1/assessments</span> - Create assessment</li>
+                                <li><span class="api-url">GET /api/v1/students/{student_id}/assessments</span> - List student assessments</li>
+                            </ul>
+                        </div>
+                        
+                        <div class="mb-3">
+                            <h6>Content Adaptation</h6>
+                            <ul>
+                                <li><span class="api-url">POST /api/v1/content/adapt</span> - Adapt content for a student</li>
+                            </ul>
+                        </div>
+                        
+                        <div class="mb-3">
+                            <h6>Learning Paths</h6>
+                            <ul>
+                                <li><span class="api-url">GET /api/v1/learning-paths/{student_id}</span> - Get personalized learning path</li>
+                            </ul>
+                        </div>
+                        
+                        <div class="mb-3">
+                            <h6>Models</h6>
+                            <ul>
+                                <li><span class="api-url">GET /api/v1/models</span> - List available models</li>
+                                <li><span class="api-url">GET /api/v1/models/{model_name}/capabilities</span> - Get model capabilities</li>
+                            </ul>
+                        </div>
+                        
+                        <p class="mt-4">
+                            For complete API documentation, visit the <a href="/docs" target="_blank">Swagger UI</a> or 
+                            <a href="/redoc" target="_blank">ReDoc</a> pages.
+                        </p>
+                    </div>
+                </div>
+            </div>
+        </div>
+    </div>
+
+    <footer class="footer">
+        <div class="container">
+            <div class="row">
+                <div class="col-md-6">
+                    <h5>MCP EdTech Project</h5>
+                    <p>An open-source implementation of the Model Context Protocol for educational technology applications.</p>
+                </div>
+                <div class="col-md-6 text-md-end">
+                    <p>© 2025 MCP EdTech Project</p>
+                    <p>Licensed under MIT License</p>
+                </div>
+            </div>
+        </div>
+    </footer>
+
+    <script src="https://cdn.jsdelivr.net/npm/bootstrap@5.3.0-alpha1/dist/js/bootstrap.bundle.min.js"></script>
+    <script>
+        // Store context and student IDs
+        let currentContextId = null;
+        let currentStudentId = null;
+
+        // Function to format JSON responses
+        function formatJSON(json) {
+            return JSON.stringify(json, null, 2);
+        }
+
+        // Create Context
+        document.getElementById('createContextBtn').addEventListener('click', async () => {
+            const loadingElement = document.getElementById('loading-context');
+            loadingElement.style.display = 'inline';
+            
+            try {
+                const response = await fetch('/api/v1/context/create', {
+                    method: 'POST',
+                    headers: {
+                        'Content-Type': 'application/json'
+                    },
+                    body: JSON.stringify({
+                        metadata: {
+                            source: 'demo-ui',
+                            created_by: 'demo-user'
+                        }
+                    })
+                });
+                
+                const data = await response.json();
+                currentContextId = data.context_id;
+                
+                document.getElementById('contextResponse').innerText = formatJSON(data);
+            } catch (error) {
+                document.getElementById('contextResponse').innerText = `Error: ${error.message}`;
+            } finally {
+                loadingElement.style.display = 'none';
+            }
+        });
+
+        // Process Interaction
+        document.getElementById('interactBtn').addEventListener('click', async () => {
+            if (!currentContextId) {
+                alert('Please create a context first!');
+                return;
+            }
+            
+            const interactionText = document.getElementById('interactionText').value;
+            if (!interactionText) {
+                alert('Please enter a question or prompt!');
+                return;
+            }
+            
+            const loadingElement = document.getElementById('loading-interaction');
+            loadingElement.style.display = 'inline';
+            
+            try {
+                const response = await fetch('/api/v1/interact', {
+                    method: 'POST',
+                    headers: {
+                        'Content-Type': 'application/json'
+                    },
+                    body: JSON.stringify({
+                        context_id: currentContextId,
+                        interaction_type: 'text',
+                        content: {
+                            text: interactionText
+                        },
+                        format: 'text',
+                        model_name: 'mock'
+                    })
+                });
+                
+                const data = await response.json();
+                document.getElementById('interactionResponse').innerText = formatJSON(data);
+            } catch (error) {
+                document.getElementById('interactionResponse').innerText = `Error: ${error.message}`;
+            } finally {
+                loadingElement.style.display = 'none';
+            }
+        });
+
+        // Create Student Profile
+        document.getElementById('createStudentBtn').addEventListener('click', async () => {
+            const studentName = document.getElementById('studentName').value;
+            if (!studentName) {
+                alert('Please enter a student name!');
+                return;
+            }
+            
+            const educationalLevel = document.getElementById('educationalLevel').value;
+            
+            const loadingElement = document.getElementById('loading-student');
+            loadingElement.style.display = 'inline';
+            
+            try {
+                const response = await fetch('/api/v1/students', {
+                    method: 'POST',
+                    headers: {
+                        'Content-Type': 'application/json'
+                    },
+                    body: JSON.stringify({
+                        name: studentName,
+                        educational_level: educationalLevel,
+                        learning_style: 'visual',
+                        interests: ['science', 'technology', 'art'],
+                        strengths: ['problem-solving', 'creativity'],
+                        areas_for_improvement: ['time-management']
+                    })
+                });
+                
+                const data = await response.json();
+                currentStudentId = data.id;
+                
+                document.getElementById('studentResponse').innerText = formatJSON(data);
+            } catch (error) {
+                document.getElementById('studentResponse').innerText = `Error: ${error.message}`;
+            } finally {
+                loadingElement.style.display = 'none';
+            }
+        });
+
+        // Adapt Content
+        document.getElementById('adaptContentBtn').addEventListener('click', async () => {
+            if (!currentStudentId) {
+                alert('Please create a student profile first!');
+                return;
+            }
+            
+            const contentText = document.getElementById('contentText').value;
+            if (!contentText) {
+                alert('Please enter content to adapt!');
+                return;
+            }
+            
+            const loadingElement = document.getElementById('loading-content');
+            loadingElement.style.display = 'inline';
+            
+            try {
+                const response = await fetch('/api/v1/content/adapt', {
+                    method: 'POST',
+                    headers: {
+                        'Content-Type': 'application/json'
+                    },
+                    body: JSON.stringify({
+                        content: {
+                            text: contentText
+                        },
+                        student_id: currentStudentId,
+                        learning_objectives: ['obj-1', 'obj-2'],
+                        content_format: 'text'
+                    })
+                });
+                
+                const data = await response.json();
+                document.getElementById('contentResponse').innerText = formatJSON(data);
+            } catch (error) {
+                document.getElementById('contentResponse').innerText = `Error: ${error.message}`;
+            } finally {
+                loadingElement.style.display = 'none';
+            }
+        });
+    </script>
+</body>
+</html>
+"""
+
+# Write the index.html file
+with open(static_dir / "index.html", "w") as f:
+    f.write(index_html)
+
+print(f"Demo UI created at {static_dir / 'index.html'}")

src/edtech_extensions/assessment.py

@@ -0,0 +1,596 @@
+"""
+EdTech Extensions - Assessment and Feedback System
+
+This module provides functionality for creating and managing assessments,
+as well as generating personalized feedback for students.
+"""
+
+from typing import Dict, List, Optional, Any, Union
+import os
+import json
+from datetime import datetime
+from enum import Enum
+from uuid import uuid4
+
+from pydantic import BaseModel, Field
+
+
+class QuestionType(str, Enum):
+    """Types of questions supported in assessments."""
+    MULTIPLE_CHOICE = "multiple_choice"
+    TRUE_FALSE = "true_false"
+    SHORT_ANSWER = "short_answer"
+    ESSAY = "essay"
+    MATCHING = "matching"
+    FILL_BLANK = "fill_blank"
+
+
+class Question(BaseModel):
+    """Model representing an assessment question."""
+    id: str = Field(..., description="Unique identifier for this question")
+    type: QuestionType = Field(..., description="Type of question")
+    text: str = Field(..., description="Question text")
+    options: List[Dict[str, Any]] = Field(default_factory=list, description="Answer options for multiple choice, etc.")
+    correct_answer: Any = Field(..., description="Correct answer or answers")
+    points: int = Field(1, description="Points for this question")
+    difficulty: str = Field("medium", description="Question difficulty")
+    tags: List[str] = Field(default_factory=list, description="Tags for categorizing questions")
+    explanation: str = Field("", description="Explanation of the correct answer")
+
+
+class Assessment(BaseModel):
+    """Model representing an assessment."""
+    id: str = Field(..., description="Unique identifier for this assessment")
+    title: str = Field(..., description="Assessment title")
+    description: str = Field("", description="Assessment description")
+    questions: List[Question] = Field(..., description="Questions in this assessment")
+    time_limit_minutes: Optional[int] = Field(None, description="Time limit in minutes, if any")
+    passing_score: float = Field(70.0, description="Passing score percentage")
+    tags: List[str] = Field(default_factory=list, description="Tags for categorizing assessments")
+    learning_objectives: List[str] = Field(default_factory=list, description="Learning objectives covered")
+    created_at: str = Field(..., description="Creation timestamp")
+
+
+class StudentResponse(BaseModel):
+    """Model representing a student's response to a question."""
+    question_id: str = Field(..., description="ID of the question")
+    student_answer: Any = Field(..., description="Student's answer")
+    is_correct: Optional[bool] = Field(None, description="Whether the answer is correct")
+    points_earned: Optional[float] = Field(None, description="Points earned for this response")
+    feedback: str = Field("", description="Feedback on this response")
+
+
+class AssessmentSubmission(BaseModel):
+    """Model representing a student's assessment submission."""
+    id: str = Field(..., description="Unique identifier for this submission")
+    assessment_id: str = Field(..., description="ID of the assessment")
+    student_id: str = Field(..., description="ID of the student")
+    responses: List[StudentResponse] = Field(..., description="Student's responses")
+    start_time: str = Field(..., description="Start timestamp")
+    end_time: str = Field(..., description="End timestamp")
+    score: Optional[float] = Field(None, description="Overall score")
+    feedback: str = Field("", description="Overall feedback")
+    graded: bool = Field(False, description="Whether the submission has been graded")
+
+
+class AssessmentSystem:
+    """
+    Manages assessments and student submissions.
+    
+    This class provides functionality for creating, retrieving, and grading
+    assessments, as well as generating personalized feedback.
+    """
+    
+    def __init__(self, storage_dir: str = "./storage/assessments"):
+        """
+        Initialize a new AssessmentSystem.
+        
+        Args:
+            storage_dir: Directory to store assessment data in.
+        """
+        self.storage_dir = storage_dir
+        self.assessments_dir = os.path.join(storage_dir, "definitions")
+        self.submissions_dir = os.path.join(storage_dir, "submissions")
+        
+        os.makedirs(self.assessments_dir, exist_ok=True)
+        os.makedirs(self.submissions_dir, exist_ok=True)
+        
+    def _get_assessment_path(self, assessment_id: str) -> str:
+        """
+        Get the file path for an assessment.
+        
+        Args:
+            assessment_id: The ID of the assessment.
+            
+        Returns:
+            The file path for the assessment.
+        """
+        return os.path.join(self.assessments_dir, f"{assessment_id}.json")
+        
+    def _get_submission_path(self, submission_id: str) -> str:
+        """
+        Get the file path for a submission.
+        
+        Args:
+            submission_id: The ID of the submission.
+            
+        Returns:
+            The file path for the submission.
+        """
+        return os.path.join(self.submissions_dir, f"{submission_id}.json")
+    
+    async def create_assessment(
+        self,
+        title: str,
+        questions: List[Question],
+        description: str = "",
+        time_limit_minutes: Optional[int] = None,
+        passing_score: float = 70.0,
+        tags: List[str] = None,
+        learning_objectives: List[str] = None
+    ) -> Assessment:
+        """
+        Create a new assessment.
+        
+        Args:
+            title: Assessment title.
+            questions: List of questions.
+            description: Assessment description.
+            time_limit_minutes: Time limit in minutes, if any.
+            passing_score: Passing score percentage.
+            tags: Tags for categorizing the assessment.
+            learning_objectives: Learning objectives covered.
+            
+        Returns:
+            The newly created Assessment.
+        """
+        assessment_id = str(uuid4())
+        created_at = datetime.utcnow().isoformat()
+        
+        assessment = Assessment(
+            id=assessment_id,
+            title=title,
+            description=description,
+            questions=questions,
+            time_limit_minutes=time_limit_minutes,
+            passing_score=passing_score,
+            tags=tags or [],
+            learning_objectives=learning_objectives or [],
+            created_at=created_at
+        )
+        
+        # Save to disk
+        await self._save_assessment(assessment)
+        
+        return assessment
+    
+    async def _save_assessment(self, assessment: Assessment) -> bool:
+        """
+        Save an assessment to disk.
+        
+        Args:
+            assessment: The Assessment to save.
+            
+        Returns:
+            True if the save was successful, False otherwise.
+        """
+        try:
+            with open(self._get_assessment_path(assessment.id), 'w') as f:
+                json.dump(assessment.dict(), f, indent=2)
+            return True
+        except Exception as e:
+            print(f"Error saving assessment: {e}")
+            return False
+    
+    async def get_assessment(self, assessment_id: str) -> Optional[Assessment]:
+        """
+        Get an assessment by ID.
+        
+        Args:
+            assessment_id: The ID of the assessment.
+            
+        Returns:
+            The Assessment if found, None otherwise.
+        """
+        try:
+            path = self._get_assessment_path(assessment_id)
+            if not os.path.exists(path):
+                return None
+                
+            with open(path, 'r') as f:
+                data = json.load(f)
+                
+            return Assessment(**data)
+        except Exception as e:
+            print(f"Error loading assessment: {e}")
+            return None
+    
+    async def list_assessments(
+        self,
+        tags: Optional[List[str]] = None,
+        learning_objectives: Optional[List[str]] = None
+    ) -> List[Assessment]:
+        """
+        List assessments, optionally filtered.
+        
+        Args:
+            tags: Optional filter by tags.
+            learning_objectives: Optional filter by learning objectives.
+            
+        Returns:
+            List of Assessment objects.
+        """
+        assessments = []
+        
+        try:
+            for filename in os.listdir(self.assessments_dir):
+                if filename.endswith('.json'):
+                    path = os.path.join(self.assessments_dir, filename)
+                    
+                    with open(path, 'r') as f:
+                        data = json.load(f)
+                        
+                    assessment = Assessment(**data)
+                    
+                    # Apply filters
+                    include = True
+                    
+                    if tags:
+                        # Include if any tag matches
+                        tag_match = any(tag in assessment.tags for tag in tags)
+                        if not tag_match:
+                            include = False
+                            
+                    if learning_objectives:
+                        # Include if any learning objective matches
+                        obj_match = any(obj in assessment.learning_objectives for obj in learning_objectives)
+                        if not obj_match:
+                            include = False
+                            
+                    if include:
+                        assessments.append(assessment)
+        except Exception as e:
+            print(f"Error listing assessments: {e}")
+            
+        return assessments
+    
+    async def submit_assessment(
+        self,
+        assessment_id: str,
+        student_id: str,
+        responses: List[StudentResponse]
+    ) -> AssessmentSubmission:
+        """
+        Submit an assessment.
+        
+        Args:
+            assessment_id: ID of the assessment.
+            student_id: ID of the student.
+            responses: List of student responses.
+            
+        Returns:
+            The AssessmentSubmission.
+        """
+        submission_id = str(uuid4())
+        start_time = datetime.utcnow().isoformat()
+        end_time = datetime.utcnow().isoformat()
+        
+        submission = AssessmentSubmission(
+            id=submission_id,
+            assessment_id=assessment_id,
+            student_id=student_id,
+            responses=responses,
+            start_time=start_time,
+            end_time=end_time,
+            score=None,
+            feedback="",
+            graded=False
+        )
+        
+        # Save to disk
+        await self._save_submission(submission)
+        
+        # Grade the submission
+        graded_submission = await self.grade_submission(submission_id)
+        
+        return graded_submission
+    
+    async def _save_submission(self, submission: AssessmentSubmission) -> bool:
+        """
+        Save a submission to disk.
+        
+        Args:
+            submission: The AssessmentSubmission to save.
+            
+        Returns:
+            True if the save was successful, False otherwise.
+        """
+        try:
+            with open(self._get_submission_path(submission.id), 'w') as f:
+                json.dump(submission.dict(), f, indent=2)
+            return True
+        except Exception as e:
+            print(f"Error saving submission: {e}")
+            return False
+    
+    async def get_submission(self, submission_id: str) -> Optional[AssessmentSubmission]:
+        """
+        Get a submission by ID.
+        
+        Args:
+            submission_id: The ID of the submission.
+            
+        Returns:
+            The AssessmentSubmission if found, None otherwise.
+        """
+        try:
+            path = self._get_submission_path(submission_id)
+            if not os.path.exists(path):
+                return None
+                
+            with open(path, 'r') as f:
+                data = json.load(f)
+                
+            return AssessmentSubmission(**data)
+        except Exception as e:
+            print(f"Error loading submission: {e}")
+            return None
+    
+    async def grade_submission(self, submission_id: str) -> Optional[AssessmentSubmission]:
+        """
+        Grade a submission.
+        
+        Args:
+            submission_id: The ID of the submission.
+            
+        Returns:
+            The graded AssessmentSubmission if found, None otherwise.
+        """
+        submission = await self.get_submission(submission_id)
+        if not submission:
+            return None
+            
+        assessment = await self.get_assessment(submission.assessment_id)
+        if not assessment:
+            return None
+            
+        # Create a map of questions by ID for easy lookup
+        questions_map = {q.id: q for q in assessment.questions}
+        
+        total_points = 0
+        earned_points = 0
+        
+        # Grade each response
+        for response in submission.responses:
+            question = questions_map.get(response.question_id)
+            if not question:
+                continue
+                
+            total_points += question.points
+            
+            # Grade based on question type
+            if question.type == QuestionType.MULTIPLE_CHOICE or question.type == QuestionType.TRUE_FALSE:
+                # Simple equality check
+                is_correct = response.student_answer == question.correct_answer
+                points_earned = question.points if is_correct else 0
+                
+                response.is_correct = is_correct
+                response.points_earned = points_earned
+                response.feedback = question.explanation if question.explanation else (
+                    "Correct!" if is_correct else f"Incorrect. The correct answer is: {question.correct_answer}"
+                )
+                
+            elif question.type == QuestionType.FILL_BLANK:
+                # Case-insensitive equality check
+                is_correct = str(response.student_answer).lower() == str(question.correct_answer).lower()
+                points_earned = question.points if is_correct else 0
+                
+                response.is_correct = is_correct
+                response.points_earned = points_earned
+                response.feedback = question.explanation if question.explanation else (
+                    "Correct!" if is_correct else f"Incorrect. The correct answer is: {question.correct_answer}"
+                )
+                
+            elif question.type == QuestionType.SHORT_ANSWER:
+                # For short answer, we'll use a simple keyword check
+                # In a real implementation, this would use more sophisticated NLP techniques
+                student_answer = str(response.student_answer).lower()
+                correct_keywords = [str(k).lower() for k in question.correct_answer]
+                
+                # Check how many keywords are present
+                matches = sum(1 for k in correct_keywords if k in student_answer)
+                match_ratio = matches / len(correct_keywords) if correct_keywords else 0
+                
+                # Full points if all keywords present, partial otherwise
+                is_correct = match_ratio >= 0.7  # 70% or more keywords
+                points_earned = question.points * match_ratio
+                
+                response.is_correct = is_correct
+                response.points_earned = points_earned
+                response.feedback = question.explanation if question.explanation else (
+                    "Good answer!" if is_correct else 
+                    f"Your answer could be improved. Important concepts to include: {', '.join(correct_keywords)}"
+                )
+                
+            elif question.type == QuestionType.ESSAY:
+                # For essays, we'll mark as needing manual grading
+                # In a real implementation, this might use AI for initial grading
+                response.is_correct = None
+                response.points_earned = None
+                response.feedback = "This response requires manual grading."
+                
+            elif question.type == QuestionType.MATCHING:
+                # Check if all matches are correct
+                correct_matches = question.correct_answer
+                student_matches = response.student_answer
+                
+                # Count correct matches
+                correct_count = sum(1 for k, v in student_matches.items() if k in correct_matches and correct_matches[k] == v)
+                total_matches = len(correct_matches)
+                
+                match_ratio = correct_count / total_matches if total_matches else 0
+                is_correct = match_ratio >= 0.7  # 70% or more correct
+                points_earned = question.points * match_ratio
+                
+                response.is_correct = is_correct
+                response.points_earned = points_earned
+                response.feedback = question.explanation if question.explanation else (
+                    "Good matching!" if is_correct else 
+                    f"Some matches were incorrect. Please review the correct answers."
+                )
+                
+            # Add to total points
+            if response.points_earned is not None:
+                earned_points += response.points_earned
+        
+        # Calculate overall score
+        score_percentage = (earned_points / total_points * 100) if total_points > 0 else 0
+        
+        # Generate overall feedback
+        if score_percentage >= assessment.passing_score:
+            overall_feedback = f"Congratulations! You passed with a score of {score_percentage:.1f}%."
+        else:
+            overall_feedback = f"You scored {score_percentage:.1f}%, which is below the passing score of {assessment.passing_score}%. Please review the material and try again."
+            
+        # Update submission
+        submission.score = score_percentage
+        submission.feedback = overall_feedback
+        submission.graded = True
+        
+        # Save updated submission
+        await self._save_submission(submission)
+        
+        return submission
+    
+    async def list_student_submissions(self, student_id: str) -> List[AssessmentSubmission]:
+        """
+        List submissions for a student.
+        
+        Args:
+            student_id: ID of the student.
+            
+        Returns:
+            List of AssessmentSubmission objects.
+        """
+        submissions = []
+        
+        try:
+            for filename in os.listdir(self.submissions_dir):
+                if filename.endswith('.json'):
+                    path = os.path.join(self.submissions_dir, filename)
+                    
+                    with open(path, 'r') as f:
+                        data = json.load(f)
+                        
+                    if data.get("student_id") == student_id:
+                        submissions.append(AssessmentSubmission(**data))
+        except Exception as e:
+            print(f"Error listing submissions: {e}")
+            
+        # Sort by end time, newest first
+        submissions.sort(key=lambda x: x.end_time, reverse=True)
+        return submissions
+    
+    async def generate_feedback_report(self, submission_id: str) -> Dict[str, Any]:
+        """
+        Generate a detailed feedback report for a submission.
+        
+        Args:
+            submission_id: ID of the submission.
+            
+        Returns:
+            Dictionary containing the feedback report.
+        """
+        submission = await self.get_submission(submission_id)
+        if not submission:
+            return {"error": "Submission not found"}
+            
+        assessment = await self.get_assessment(submission.assessment_id)
+        if not assessment:
+            return {"error": "Assessment not found"}
+            
+        # Create a map of questions by ID for easy lookup
+        questions_map = {q.id: q for q in assessment.questions}
+        
+        # Group questions and responses by tags
+        tag_groups = {}
+        for response in submission.responses:
+            question = questions_map.get(response.question_id)
+            if not question:
+                continue
+                
+            for tag in question.tags:
+                if tag not in tag_groups:
+                    tag_groups[tag] = {
+                        "total": 0,
+                        "correct": 0,
+                        "questions": []
+                    }
+                    
+                tag_groups[tag]["total"] += 1
+                if response.is_correct:
+                    tag_groups[tag]["correct"] += 1
+                    
+                tag_groups[tag]["questions"].append({
+                    "question_text": question.text,
+                    "student_answer": response.student_answer,
+                    "correct_answer": question.correct_answer,
+                    "is_correct": response.is_correct,
+                    "feedback": response.feedback
+                })
+        
+        # Generate strengths and weaknesses
+        strengths = []
+        weaknesses = []
+        
+        for tag, data in tag_groups.items():
+            score = data["correct"] / data["total"] if data["total"] > 0 else 0
+            
+            if score >= 0.8:  # 80% or better
+                strengths.append({
+                    "topic": tag,
+                    "score": score * 100,
+                    "comment": f"You show strong understanding of {tag}."
+                })
+            elif score <= 0.6:  # 60% or worse
+                weaknesses.append({
+                    "topic": tag,
+                    "score": score * 100,
+                    "comment": f"You may need additional practice with {tag}."
+                })
+        
+        # Generate recommended resources (in a real app, these would come from a database)
+        recommended_resources = []
+        for weakness in weaknesses:
+            recommended_resources.append({
+                "topic": weakness["topic"],
+                "title": f"Review material on {weakness['topic']}",
+                "type": "article",
+                "url": f"https://example.com/resources/{weakness['topic'].lower().replace(' ', '-')}"
+            })
+        
+        # Create the report
+        report = {
+            "submission_id": submission_id,
+            "assessment_id": submission.assessment_id,
+            "assessment_title": assessment.title,
+            "student_id": submission.student_id,
+            "score": submission.score,
+            "passing_score": assessment.passing_score,
+            "passed": submission.score >= assessment.passing_score if submission.score is not None else False,
+            "strengths": strengths,
+            "weaknesses": weaknesses,
+            "topic_breakdown": [
+                {
+                    "topic": tag,
+                    "score": (data["correct"] / data["total"] * 100) if data["total"] > 0 else 0,
+                    "questions_count": data["total"]
+                }
+                for tag, data in tag_groups.items()
+            ],
+            "recommended_resources": recommended_resources,
+            "detailed_feedback": submission.feedback,
+            "generated_at": datetime.utcnow().isoformat()
+        }
+        
+        return report

src/edtech_extensions/content_adaptation.py

@@ -0,0 +1,267 @@
+"""
+EdTech Extensions - Content Adaptation
+
+This module provides functionality for adapting educational content
+based on student profiles and learning objectives.
+"""
+
+from typing import Dict, List, Optional, Any, Union
+import os
+import json
+from datetime import datetime
+
+from ..mcp_core.protocol import StudentProfile, LearningObjective, EducationalLevel, ContentFormat
+
+
+class ContentAdapter:
+    """
+    Adapts educational content based on student profiles and learning objectives.
+    
+    This class provides functionality for personalizing educational content
+    to match a student's learning style, educational level, and interests.
+    """
+    
+    def __init__(self):
+        """Initialize a new ContentAdapter."""
+        pass
+        
+    async def adapt_content(
+        self,
+        content: Dict[str, Any],
+        student_profile: StudentProfile,
+        learning_objectives: List[LearningObjective],
+        content_format: ContentFormat = ContentFormat.TEXT
+    ) -> Dict[str, Any]:
+        """
+        Adapt educational content for a specific student.
+        
+        Args:
+            content: Original content to adapt.
+            student_profile: Student profile to adapt content for.
+            learning_objectives: Learning objectives for this content.
+            content_format: Format of the content.
+            
+        Returns:
+            Dictionary containing adapted content and metadata.
+        """
+        # In a real implementation, this would use AI models to adapt content
+        # based on the student profile and learning objectives.
+        # For this demo, we'll implement a simplified version.
+        
+        original_text = content.get("text", "")
+        
+        # Apply adaptations based on educational level
+        adapted_text = self._adapt_for_educational_level(
+            original_text,
+            student_profile.educational_level
+        )
+        
+        # Apply adaptations based on learning style
+        adapted_text = self._adapt_for_learning_style(
+            adapted_text,
+            student_profile.learning_style
+        )
+        
+        # Apply adaptations based on interests
+        adapted_text = self._adapt_for_interests(
+            adapted_text,
+            student_profile.interests
+        )
+        
+        # Generate recommended activities
+        recommended_activities = self._generate_recommended_activities(
+            student_profile,
+            learning_objectives
+        )
+        
+        # List adaptations applied
+        adaptations_applied = []
+        if student_profile.educational_level:
+            adaptations_applied.append(f"Adapted for {student_profile.educational_level} educational level")
+        if student_profile.learning_style:
+            adaptations_applied.append(f"Adapted for {student_profile.learning_style} learning style")
+        if student_profile.interests:
+            adaptations_applied.append("Incorporated student interests")
+            
+        return {
+            "text": adapted_text,
+            "original_text": original_text,
+            "adaptations_applied": adaptations_applied,
+            "recommended_activities": recommended_activities,
+            "format": content_format,
+            "adapted_at": datetime.utcnow().isoformat()
+        }
+        
+    def _adapt_for_educational_level(
+        self,
+        text: str,
+        educational_level: EducationalLevel
+    ) -> str:
+        """
+        Adapt content for a specific educational level.
+        
+        Args:
+            text: Original text content.
+            educational_level: Target educational level.
+            
+        Returns:
+            Adapted text content.
+        """
+        # In a real implementation, this would use more sophisticated techniques
+        # such as vocabulary adjustment, complexity reduction, etc.
+        
+        if educational_level == EducationalLevel.ELEMENTARY:
+            # Simplify language for elementary level
+            return f"{text}\n\n[Note: This content has been simplified for elementary level students.]"
+            
+        elif educational_level == EducationalLevel.MIDDLE_SCHOOL:
+            # Moderate complexity for middle school
+            return f"{text}\n\n[Note: This content has been adapted for middle school students.]"
+            
+        elif educational_level == EducationalLevel.HIGH_SCHOOL:
+            # Standard complexity for high school
+            return f"{text}\n\n[Note: This content has been adapted for high school students.]"
+            
+        elif educational_level == EducationalLevel.UNDERGRADUATE:
+            # Higher complexity for undergraduate
+            return f"{text}\n\n[Note: This content has been adapted for undergraduate students.]"
+            
+        elif educational_level == EducationalLevel.GRADUATE:
+            # Advanced complexity for graduate
+            return f"{text}\n\n[Note: This content has been adapted for graduate students with advanced terminology.]"
+            
+        elif educational_level == EducationalLevel.PROFESSIONAL:
+            # Professional terminology
+            return f"{text}\n\n[Note: This content has been adapted with professional terminology.]"
+            
+        return text
+        
+    def _adapt_for_learning_style(self, text: str, learning_style: str) -> str:
+        """
+        Adapt content for a specific learning style.
+        
+        Args:
+            text: Original text content.
+            learning_style: Target learning style.
+            
+        Returns:
+            Adapted text content.
+        """
+        # In a real implementation, this would use more sophisticated techniques
+        
+        if not learning_style:
+            return text
+            
+        if learning_style.lower() == "visual":
+            # Add visual cues
+            return f"{text}\n\n[Note: Visual diagrams and charts would be included here to support visual learners.]"
+            
+        elif learning_style.lower() == "auditory":
+            # Add auditory cues
+            return f"{text}\n\n[Note: Audio explanations would be available for auditory learners.]"
+            
+        elif learning_style.lower() == "reading":
+            # Add reading cues
+            return f"{text}\n\n[Note: Additional reading materials and references are provided for reading-oriented learners.]"
+            
+        elif learning_style.lower() == "kinesthetic":
+            # Add kinesthetic cues
+            return f"{text}\n\n[Note: Interactive exercises would be included here for kinesthetic learners.]"
+            
+        return text
+        
+    def _adapt_for_interests(self, text: str, interests: List[str]) -> str:
+        """
+        Adapt content to incorporate student interests.
+        
+        Args:
+            text: Original text content.
+            interests: List of student interests.
+            
+        Returns:
+            Adapted text content.
+        """
+        # In a real implementation, this would use more sophisticated techniques
+        
+        if not interests:
+            return text
+            
+        interest_note = f"\n\n[Note: This content would include examples related to your interests in {', '.join(interests)}.]"
+        return text + interest_note
+        
+    def _generate_recommended_activities(
+        self,
+        student_profile: StudentProfile,
+        learning_objectives: List[LearningObjective]
+    ) -> List[Dict[str, Any]]:
+        """
+        Generate recommended activities based on student profile and learning objectives.
+        
+        Args:
+            student_profile: Student profile.
+            learning_objectives: Learning objectives.
+            
+        Returns:
+            List of recommended activities.
+        """
+        # In a real implementation, this would generate personalized activities
+        # based on the student's profile and learning objectives.
+        
+        activities = []
+        
+        # Add activities based on learning style
+        if student_profile.learning_style:
+            if student_profile.learning_style.lower() == "visual":
+                activities.append({
+                    "type": "visualization",
+                    "title": "Create a visual diagram",
+                    "description": "Create a diagram that visualizes the key concepts."
+                })
+            elif student_profile.learning_style.lower() == "auditory":
+                activities.append({
+                    "type": "discussion",
+                    "title": "Verbal explanation",
+                    "description": "Record yourself explaining the concept to someone else."
+                })
+            elif student_profile.learning_style.lower() == "reading":
+                activities.append({
+                    "type": "research",
+                    "title": "Research and summarize",
+                    "description": "Find additional resources on this topic and write a summary."
+                })
+            elif student_profile.learning_style.lower() == "kinesthetic":
+                activities.append({
+                    "type": "hands-on",
+                    "title": "Practical application",
+                    "description": "Complete a hands-on project applying these concepts."
+                })
+                
+        # Add activities based on learning objectives
+        for objective in learning_objectives:
+            if "remember" in objective.taxonomy_level.lower():
+                activities.append({
+                    "type": "quiz",
+                    "title": f"Quiz on {objective.subject_area}",
+                    "description": f"Test your recall of key facts about {objective.description}"
+                })
+            elif "understand" in objective.taxonomy_level.lower():
+                activities.append({
+                    "type": "explanation",
+                    "title": f"Explain {objective.subject_area} concepts",
+                    "description": f"Write an explanation of {objective.description} in your own words."
+                })
+            elif "apply" in objective.taxonomy_level.lower():
+                activities.append({
+                    "type": "problem",
+                    "title": f"Apply {objective.subject_area} knowledge",
+                    "description": f"Solve problems that require applying {objective.description}."
+                })
+            elif "analyze" in objective.taxonomy_level.lower():
+                activities.append({
+                    "type": "analysis",
+                    "title": f"Analyze {objective.subject_area}",
+                    "description": f"Analyze a case study related to {objective.description}."
+                })
+                
+        # Limit to 3 activities
+        return activities[:3]

src/edtech_extensions/progress_tracking.py

@@ -0,0 +1,450 @@
+"""
+EdTech Extensions - Learning Progress Tracking
+
+This module provides functionality for tracking student learning progress
+in the MCP EdTech system, including assessment results and skill development.
+"""
+
+import os
+from datetime import datetime
+from typing import Dict, List, Optional, Any, Set, Tuple
+from uuid import uuid4
+import json
+from enum import Enum
+
+from pydantic import BaseModel, Field
+
+
+class AssessmentType(str, Enum):
+    """Types of assessments supported by the system."""
+    QUIZ = "quiz"
+    TEST = "test"
+    ASSIGNMENT = "assignment"
+    PROJECT = "project"
+    PRACTICE = "practice"
+
+
+class AssessmentResult(BaseModel):
+    """Model representing an assessment result."""
+    id: str = Field(..., description="Unique identifier for this assessment result")
+    student_id: str = Field(..., description="ID of the student")
+    assessment_type: AssessmentType = Field(..., description="Type of assessment")
+    title: str = Field(..., description="Title of the assessment")
+    score: float = Field(..., description="Score achieved (0-100)")
+    max_score: float = Field(..., description="Maximum possible score")
+    objectives: List[str] = Field(default_factory=list, description="Learning objectives covered")
+    completed_at: str = Field(..., description="Completion timestamp")
+    feedback: str = Field("", description="Feedback on the assessment")
+    details: Dict[str, Any] = Field(default_factory=dict, description="Detailed assessment data")
+
+
+class SkillLevel(str, Enum):
+    """Skill proficiency levels."""
+    NOVICE = "novice"
+    BEGINNER = "beginner"
+    INTERMEDIATE = "intermediate"
+    ADVANCED = "advanced"
+    EXPERT = "expert"
+
+
+class SkillProgress(BaseModel):
+    """Model representing progress in a specific skill."""
+    skill_id: str = Field(..., description="Unique identifier for this skill")
+    name: str = Field(..., description="Name of the skill")
+    level: SkillLevel = Field(SkillLevel.NOVICE, description="Current skill level")
+    progress_percentage: float = Field(0.0, description="Progress towards next level (0-100)")
+    last_updated: str = Field(..., description="Last update timestamp")
+    related_objectives: List[str] = Field(default_factory=list, description="Related learning objectives")
+
+
+class ProgressTracker:
+    """
+    Tracks student learning progress in the MCP EdTech system.
+    
+    This class provides functionality for recording and analyzing student
+    progress, including assessment results and skill development.
+    """
+    
+    def __init__(self, storage_dir: str = "./storage/progress"):
+        """
+        Initialize a new ProgressTracker.
+        
+        Args:
+            storage_dir: Directory to store progress data in.
+        """
+        self.storage_dir = storage_dir
+        self.assessments_dir = os.path.join(storage_dir, "assessments")
+        self.skills_dir = os.path.join(storage_dir, "skills")
+        
+        os.makedirs(self.assessments_dir, exist_ok=True)
+        os.makedirs(self.skills_dir, exist_ok=True)
+        
+    def _get_student_assessments_dir(self, student_id: str) -> str:
+        """
+        Get the directory for a student's assessment results.
+        
+        Args:
+            student_id: The ID of the student.
+            
+        Returns:
+            The directory path.
+        """
+        path = os.path.join(self.assessments_dir, student_id)
+        os.makedirs(path, exist_ok=True)
+        return path
+        
+    def _get_student_skills_dir(self, student_id: str) -> str:
+        """
+        Get the directory for a student's skill progress.
+        
+        Args:
+            student_id: The ID of the student.
+            
+        Returns:
+            The directory path.
+        """
+        path = os.path.join(self.skills_dir, student_id)
+        os.makedirs(path, exist_ok=True)
+        return path
+    
+    async def record_assessment(
+        self,
+        student_id: str,
+        assessment_type: AssessmentType,
+        title: str,
+        score: float,
+        max_score: float,
+        objectives: List[str],
+        feedback: str = "",
+        details: Dict[str, Any] = None
+    ) -> AssessmentResult:
+        """
+        Record a new assessment result.
+        
+        Args:
+            student_id: ID of the student.
+            assessment_type: Type of assessment.
+            title: Title of the assessment.
+            score: Score achieved.
+            max_score: Maximum possible score.
+            objectives: Learning objectives covered.
+            feedback: Feedback on the assessment.
+            details: Detailed assessment data.
+            
+        Returns:
+            The newly created AssessmentResult.
+        """
+        assessment_id = str(uuid4())
+        completed_at = datetime.utcnow().isoformat()
+        
+        result = AssessmentResult(
+            id=assessment_id,
+            student_id=student_id,
+            assessment_type=assessment_type,
+            title=title,
+            score=score,
+            max_score=max_score,
+            objectives=objectives,
+            completed_at=completed_at,
+            feedback=feedback,
+            details=details or {}
+        )
+        
+        # Save to disk
+        await self._save_assessment(result)
+        
+        # Update skill progress based on assessment
+        for objective_id in objectives:
+            await self._update_skills_for_objective(
+                student_id, 
+                objective_id, 
+                score / max_score
+            )
+        
+        return result
+    
+    async def _save_assessment(self, assessment: AssessmentResult) -> bool:
+        """
+        Save an assessment result to disk.
+        
+        Args:
+            assessment: The AssessmentResult to save.
+            
+        Returns:
+            True if the save was successful, False otherwise.
+        """
+        try:
+            dir_path = self._get_student_assessments_dir(assessment.student_id)
+            file_path = os.path.join(dir_path, f"{assessment.id}.json")
+            
+            with open(file_path, 'w') as f:
+                json.dump(assessment.dict(), f, indent=2)
+            return True
+        except Exception as e:
+            print(f"Error saving assessment result: {e}")
+            return False
+    
+    async def get_assessment(
+        self,
+        student_id: str,
+        assessment_id: str
+    ) -> Optional[AssessmentResult]:
+        """
+        Get an assessment result by ID.
+        
+        Args:
+            student_id: ID of the student.
+            assessment_id: ID of the assessment.
+            
+        Returns:
+            The AssessmentResult if found, None otherwise.
+        """
+        try:
+            dir_path = self._get_student_assessments_dir(student_id)
+            file_path = os.path.join(dir_path, f"{assessment_id}.json")
+            
+            if not os.path.exists(file_path):
+                return None
+                
+            with open(file_path, 'r') as f:
+                data = json.load(f)
+                
+            return AssessmentResult(**data)
+        except Exception as e:
+            print(f"Error loading assessment result: {e}")
+            return None
+    
+    async def list_assessments(
+        self,
+        student_id: str,
+        assessment_type: Optional[AssessmentType] = None
+    ) -> List[AssessmentResult]:
+        """
+        List assessment results for a student.
+        
+        Args:
+            student_id: ID of the student.
+            assessment_type: Optional filter by assessment type.
+            
+        Returns:
+            List of AssessmentResult objects.
+        """
+        results = []
+        
+        try:
+            dir_path = self._get_student_assessments_dir(student_id)
+            
+            for filename in os.listdir(dir_path):
+                if filename.endswith('.json'):
+                    file_path = os.path.join(dir_path, filename)
+                    
+                    with open(file_path, 'r') as f:
+                        data = json.load(f)
+                        
+                    result = AssessmentResult(**data)
+                    
+                    # Apply filter if specified
+                    if assessment_type is None or result.assessment_type == assessment_type:
+                        results.append(result)
+        except Exception as e:
+            print(f"Error listing assessment results: {e}")
+            
+        # Sort by completion date, newest first
+        results.sort(key=lambda x: x.completed_at, reverse=True)
+        return results
+    
+    async def _update_skills_for_objective(
+        self,
+        student_id: str,
+        objective_id: str,
+        performance: float
+    ) -> None:
+        """
+        Update skill progress based on performance in an objective.
+        
+        Args:
+            student_id: ID of the student.
+            objective_id: ID of the learning objective.
+            performance: Performance level (0-1).
+        """
+        # In a real implementation, this would map objectives to skills
+        # and update skill progress accordingly.
+        # For this demo, we'll create/update a skill with the same ID as the objective.
+        
+        skill = await self.get_skill_progress(student_id, objective_id)
+        
+        if skill:
+            # Update existing skill
+            new_progress = skill.progress_percentage + (performance * 20)  # Increase by up to 20%
+            
+            # Check if we should level up
+            if new_progress >= 100:
+                # Level up and reset progress
+                levels = list(SkillLevel)
+                current_index = levels.index(skill.level)
+                
+                if current_index < len(levels) - 1:
+                    # Move to next level
+                    skill.level = levels[current_index + 1]
+                    skill.progress_percentage = new_progress - 100
+                else:
+                    # Already at max level
+                    skill.progress_percentage = 100
+            else:
+                skill.progress_percentage = new_progress
+                
+            skill.last_updated = datetime.utcnow().isoformat()
+        else:
+            # Create new skill
+            skill = SkillProgress(
+                skill_id=objective_id,
+                name=f"Skill for objective {objective_id}",  # In a real app, would use actual skill name
+                level=SkillLevel.NOVICE,
+                progress_percentage=performance * 20,  # Initial progress based on performance
+                last_updated=datetime.utcnow().isoformat(),
+                related_objectives=[objective_id]
+            )
+            
+        await self._save_skill_progress(student_id, skill)
+    
+    async def _save_skill_progress(
+        self,
+        student_id: str,
+        skill: SkillProgress
+    ) -> bool:
+        """
+        Save skill progress to disk.
+        
+        Args:
+            student_id: ID of the student.
+            skill: The SkillProgress to save.
+            
+        Returns:
+            True if the save was successful, False otherwise.
+        """
+        try:
+            dir_path = self._get_student_skills_dir(student_id)
+            file_path = os.path.join(dir_path, f"{skill.skill_id}.json")
+            
+            with open(file_path, 'w') as f:
+                json.dump(skill.dict(), f, indent=2)
+            return True
+        except Exception as e:
+            print(f"Error saving skill progress: {e}")
+            return False
+    
+    async def get_skill_progress(
+        self,
+        student_id: str,
+        skill_id: str
+    ) -> Optional[SkillProgress]:
+        """
+        Get skill progress by ID.
+        
+        Args:
+            student_id: ID of the student.
+            skill_id: ID of the skill.
+            
+        Returns:
+            The SkillProgress if found, None otherwise.
+        """
+        try:
+            dir_path = self._get_student_skills_dir(student_id)
+            file_path = os.path.join(dir_path, f"{skill_id}.json")
+            
+            if not os.path.exists(file_path):
+                return None
+                
+            with open(file_path, 'r') as f:
+                data = json.load(f)
+                
+            return SkillProgress(**data)
+        except Exception as e:
+            print(f"Error loading skill progress: {e}")
+            return None
+    
+    async def list_skills(self, student_id: str) -> List[SkillProgress]:
+        """
+        List skill progress for a student.
+        
+        Args:
+            student_id: ID of the student.
+            
+        Returns:
+            List of SkillProgress objects.
+        """
+        skills = []
+        
+        try:
+            dir_path = self._get_student_skills_dir(student_id)
+            
+            if os.path.exists(dir_path):
+                for filename in os.listdir(dir_path):
+                    if filename.endswith('.json'):
+                        file_path = os.path.join(dir_path, filename)
+                        
+                        with open(file_path, 'r') as f:
+                            data = json.load(f)
+                            
+                        skills.append(SkillProgress(**data))
+        except Exception as e:
+            print(f"Error listing skill progress: {e}")
+            
+        # Sort by level and then by progress percentage
+        skills.sort(
+            key=lambda x: (list(SkillLevel).index(x.level), x.progress_percentage),
+            reverse=True
+        )
+        return skills
+    
+    async def get_progress_summary(self, student_id: str) -> Dict[str, Any]:
+        """
+        Get a summary of a student's learning progress.
+        
+        Args:
+            student_id: ID of the student.
+            
+        Returns:
+            Dictionary containing progress summary.
+        """
+        assessments = await self.list_assessments(student_id)
+        skills = await self.list_skills(student_id)
+        
+        # Calculate assessment statistics
+        total_assessments = len(assessments)
+        average_score = 0
+        assessment_types_count = {}
+        recent_assessments = []
+        
+        if total_assessments > 0:
+            total_score_percentage = 0
+            
+            for assessment in assessments:
+                score_percentage = (assessment.score / assessment.max_score) * 100
+                total_score_percentage += score_percentage
+                
+                # Count by type
+                assessment_type = assessment.assessment_type
+                assessment_types_count[assessment_type] = assessment_types_count.get(assessment_type, 0) + 1
+                
+            average_score = total_score_percentage / total_assessments
+            recent_assessments = [a.dict() for a in assessments[:5]]  # 5 most recent
+            
+        # Summarize skills
+        skill_levels = {}
+        for skill in skills:
+            level = skill.level
+            skill_levels[level] = skill_levels.get(level, 0) + 1
+            
+        # Create summary
+        return {
+            "student_id": student_id,
+            "total_assessments": total_assessments,
+            "average_score": round(average_score, 2),
+            "assessment_types_count": assessment_types_count,
+            "recent_assessments": recent_assessments,
+            "total_skills": len(skills),
+            "skill_levels": skill_levels,
+            "top_skills": [s.dict() for s in skills[:3]],  # 3 highest-level skills
+            "generated_at": datetime.utcnow().isoformat()
+        }

src/edtech_extensions/student_profile.py

@@ -0,0 +1,289 @@
+"""
+EdTech Extensions - Student Profile Management
+
+This module provides functionality for managing student profiles in the MCP EdTech system.
+It includes classes and functions for creating, retrieving, updating, and analyzing student profiles.
+"""
+
+from datetime import datetime
+from typing import Dict, List, Optional, Any, Set
+from uuid import uuid4
+import json
+import os
+from enum import Enum
+
+from pydantic import BaseModel, Field
+
+from ..mcp_core.protocol import EducationalLevel, LearningObjective, StudentProfile
+
+
+class LearningStyle(str, Enum):
+    """Learning styles for student profile customization."""
+    VISUAL = "visual"
+    AUDITORY = "auditory"
+    READING = "reading"
+    KINESTHETIC = "kinesthetic"
+
+
+class StudentProfileManager:
+    """
+    Manages student profiles in the MCP EdTech system.
+    
+    This class provides functionality for creating, retrieving, updating,
+    and analyzing student profiles.
+    """
+    
+    def __init__(self, storage_dir: str = "./storage/students"):
+        """
+        Initialize a new StudentProfileManager.
+        
+        Args:
+            storage_dir: Directory to store student profiles in.
+        """
+        self.storage_dir = storage_dir
+        os.makedirs(storage_dir, exist_ok=True)
+        self.profiles: Dict[str, StudentProfile] = {}
+        
+    def _get_profile_path(self, student_id: str) -> str:
+        """
+        Get the file path for a student profile.
+        
+        Args:
+            student_id: The ID of the student.
+            
+        Returns:
+            The file path for the student profile.
+        """
+        return os.path.join(self.storage_dir, f"{student_id}.json")
+    
+    async def create_profile(
+        self,
+        name: str,
+        educational_level: EducationalLevel,
+        learning_style: Optional[str] = None,
+        interests: Optional[List[str]] = None,
+        strengths: Optional[List[str]] = None,
+        areas_for_improvement: Optional[List[str]] = None
+    ) -> StudentProfile:
+        """
+        Create a new student profile.
+        
+        Args:
+            name: Student's name.
+            educational_level: Student's educational level.
+            learning_style: Student's preferred learning style.
+            interests: Student's interests.
+            strengths: Student's academic strengths.
+            areas_for_improvement: Areas where the student needs improvement.
+            
+        Returns:
+            The newly created StudentProfile.
+        """
+        student_id = str(uuid4())
+        
+        profile = StudentProfile(
+            id=student_id,
+            name=name,
+            educational_level=educational_level,
+            learning_style=learning_style or "",
+            interests=interests or [],
+            strengths=strengths or [],
+            areas_for_improvement=areas_for_improvement or [],
+            completed_objectives=[],
+            current_objectives=[]
+        )
+        
+        # Save to memory and disk
+        self.profiles[student_id] = profile
+        await self._save_profile(profile)
+        
+        return profile
+    
+    async def _save_profile(self, profile: StudentProfile) -> bool:
+        """
+        Save a student profile to disk.
+        
+        Args:
+            profile: The StudentProfile to save.
+            
+        Returns:
+            True if the save was successful, False otherwise.
+        """
+        try:
+            with open(self._get_profile_path(profile.id), 'w') as f:
+                json.dump(profile.dict(), f, indent=2)
+            return True
+        except Exception as e:
+            print(f"Error saving student profile: {e}")
+            return False
+    
+    async def get_profile(self, student_id: str) -> Optional[StudentProfile]:
+        """
+        Get a student profile by ID.
+        
+        Args:
+            student_id: The ID of the student.
+            
+        Returns:
+            The StudentProfile if found, None otherwise.
+        """
+        # Check memory cache first
+        if student_id in self.profiles:
+            return self.profiles[student_id]
+            
+        # Try to load from disk
+        try:
+            path = self._get_profile_path(student_id)
+            if not os.path.exists(path):
+                return None
+                
+            with open(path, 'r') as f:
+                data = json.load(f)
+                
+            profile = StudentProfile(**data)
+            self.profiles[student_id] = profile
+            return profile
+        except Exception as e:
+            print(f"Error loading student profile: {e}")
+            return None
+    
+    async def update_profile(
+        self,
+        student_id: str,
+        updates: Dict[str, Any]
+    ) -> Optional[StudentProfile]:
+        """
+        Update a student profile.
+        
+        Args:
+            student_id: The ID of the student.
+            updates: Dictionary of updates to apply.
+            
+        Returns:
+            The updated StudentProfile if found, None otherwise.
+        """
+        profile = await self.get_profile(student_id)
+        if not profile:
+            return None
+            
+        # Apply updates
+        profile_dict = profile.dict()
+        for key, value in updates.items():
+            if key in profile_dict:
+                setattr(profile, key, value)
+                
+        # Save updated profile
+        await self._save_profile(profile)
+        self.profiles[student_id] = profile
+        
+        return profile
+    
+    async def delete_profile(self, student_id: str) -> bool:
+        """
+        Delete a student profile.
+        
+        Args:
+            student_id: The ID of the student.
+            
+        Returns:
+            True if the deletion was successful, False otherwise.
+        """
+        try:
+            # Remove from memory
+            if student_id in self.profiles:
+                del self.profiles[student_id]
+                
+            # Remove from disk
+            path = self._get_profile_path(student_id)
+            if os.path.exists(path):
+                os.remove(path)
+                return True
+            return False
+        except Exception as e:
+            print(f"Error deleting student profile: {e}")
+            return False
+    
+    async def list_profiles(self) -> List[StudentProfile]:
+        """
+        List all student profiles.
+        
+        Returns:
+            List of StudentProfile objects.
+        """
+        profiles = []
+        
+        # Load all profiles from disk
+        try:
+            for filename in os.listdir(self.storage_dir):
+                if filename.endswith('.json'):
+                    student_id = filename[:-5]  # Remove .json extension
+                    profile = await self.get_profile(student_id)
+                    if profile:
+                        profiles.append(profile)
+        except Exception as e:
+            print(f"Error listing student profiles: {e}")
+            
+        return profiles
+    
+    async def add_completed_objective(
+        self,
+        student_id: str,
+        objective_id: str
+    ) -> Optional[StudentProfile]:
+        """
+        Add a completed learning objective to a student profile.
+        
+        Args:
+            student_id: The ID of the student.
+            objective_id: The ID of the completed learning objective.
+            
+        Returns:
+            The updated StudentProfile if found, None otherwise.
+        """
+        profile = await self.get_profile(student_id)
+        if not profile:
+            return None
+            
+        # Add to completed objectives if not already there
+        if objective_id not in profile.completed_objectives:
+            profile.completed_objectives.append(objective_id)
+            
+        # Remove from current objectives if present
+        if objective_id in profile.current_objectives:
+            profile.current_objectives.remove(objective_id)
+            
+        # Save updated profile
+        await self._save_profile(profile)
+        self.profiles[student_id] = profile
+        
+        return profile
+    
+    async def add_current_objective(
+        self,
+        student_id: str,
+        objective_id: str
+    ) -> Optional[StudentProfile]:
+        """
+        Add a current learning objective to a student profile.
+        
+        Args:
+            student_id: The ID of the student.
+            objective_id: The ID of the learning objective.
+            
+        Returns:
+            The updated StudentProfile if found, None otherwise.
+        """
+        profile = await self.get_profile(student_id)
+        if not profile:
+            return None
+            
+        # Add to current objectives if not already there and not completed
+        if (objective_id not in profile.current_objectives and 
+            objective_id not in profile.completed_objectives):
+            profile.current_objectives.append(objective_id)
+            
+        # Save updated profile
+        await self._save_profile(profile)
+        self.profiles[student_id] = profile
+        
+        return profile

src/mcp_core/__init__.py

@@ -0,0 +1,3 @@
+"""
+MCP Core - Model Context Protocol implementation for EdTech applications.
+"""

src/mcp_core/context.py

@@ -0,0 +1,109 @@
+from datetime import datetime
+from typing import Dict, List, Optional, Any, Union
+from uuid import uuid4
+import json
+
+
+class Context:
+    def __init__(self, context_id: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None, max_history_length: int = 100):
+        self.context_id = context_id or str(uuid4())
+        self.metadata = metadata or {}
+        self.max_history_length = max_history_length
+        self.history: List[Dict[str, Any]] = []
+        self.state: Dict[str, Any] = {}
+        self.created_at = datetime.utcnow()
+        self.updated_at = self.created_at
+        
+    def add_interaction(self, input_data: Dict[str, Any], output_data: Dict[str, Any]) -> None:
+        interaction = {
+            "timestamp": datetime.utcnow().isoformat(),
+            "input": input_data,
+            "output": output_data
+        }
+        
+        self.history.append(interaction)
+        
+        if len(self.history) > self.max_history_length:
+            self.history = self.history[-self.max_history_length:]
+            
+        self.updated_at = datetime.utcnow()
+        
+    def update_state(self, new_state: Dict[str, Any], merge: bool = True) -> None:
+        if merge:
+            self.state.update(new_state)
+        else:
+            self.state = new_state
+            
+        self.updated_at = datetime.utcnow()
+        
+    def get_history(self, limit: Optional[int] = None) -> List[Dict[str, Any]]:
+        if limit is None or limit >= len(self.history):
+            return self.history
+        return self.history[-limit:]
+    
+    def to_dict(self) -> Dict[str, Any]:
+        return {
+            "context_id": self.context_id,
+            "metadata": self.metadata,
+            "state": self.state,
+            "history": self.history,
+            "created_at": self.created_at.isoformat(),
+            "updated_at": self.updated_at.isoformat(),
+        }
+    
+    def to_json(self) -> str:
+        return json.dumps(self.to_dict())
+    
+    @classmethod
+    def from_dict(cls, data: Dict[str, Any]) -> 'Context':
+        context = cls(context_id=data.get("context_id"))
+        context.metadata = data.get("metadata", {})
+        context.state = data.get("state", {})
+        context.history = data.get("history", [])
+        
+        if "created_at" in data:
+            context.created_at = datetime.fromisoformat(data["created_at"])
+        if "updated_at" in data:
+            context.updated_at = datetime.fromisoformat(data["updated_at"])
+            
+        return context
+    
+    @classmethod
+    def from_json(cls, json_str: str) -> 'Context':
+        data = json.loads(json_str)
+        return cls.from_dict(data)
+
+
+class ContextManager:
+    def __init__(self):
+        self.contexts: Dict[str, Context] = {}
+        
+    def create_context(self, metadata: Optional[Dict[str, Any]] = None, context_id: Optional[str] = None) -> Context:
+        context = Context(context_id=context_id, metadata=metadata)
+        self.contexts[context.context_id] = context
+        return context
+    
+    def get_context(self, context_id: str) -> Optional[Context]:
+        return self.contexts.get(context_id)
+    
+    def update_context(self, context_id: str, updates: Dict[str, Any]) -> Optional[Context]:
+        context = self.get_context(context_id)
+        if not context:
+            return None
+        
+        if "metadata" in updates:
+            context.metadata.update(updates["metadata"])
+            
+        if "state" in updates:
+            context.update_state(updates["state"])
+            
+        return context
+    
+    def delete_context(self, context_id: str) -> bool:
+        if context_id in self.contexts:
+            del self.contexts[context_id]
+            return True
+        return False
+    
+    def list_contexts(self) -> List[str]:
+        return list(self.contexts.keys())

src/mcp_core/model_adapters.py

@@ -0,0 +1,313 @@
+"""
+MCP Core - Model Interface Adapters
+
+This module provides adapters for interfacing with various AI models,
+allowing the MCP system to work with different model providers and types
+while maintaining a consistent interface.
+"""
+
+from abc import ABC, abstractmethod
+from typing import Dict, Any, List, Optional, Union
+
+
+class ModelAdapter(ABC):
+    """
+    Abstract base class for model adapters.
+    
+    Model adapters provide a consistent interface for interacting with different
+    AI models, abstracting away the specifics of each model's API.
+    """
+    
+    @abstractmethod
+    async def process(self, input_data: Dict[str, Any], context: Dict[str, Any] = None) -> Dict[str, Any]:
+        """
+        Process an input with the model and return the output.
+        
+        Args:
+            input_data: The input data to process.
+            context: Optional context information to guide the model.
+            
+        Returns:
+            The model's output.
+        """
+        pass
+    
+    @abstractmethod
+    def get_capabilities(self) -> Dict[str, Any]:
+        """
+        Get the capabilities of this model.
+        
+        Returns:
+            Dictionary describing the model's capabilities.
+        """
+        pass
+
+
+class MockModelAdapter(ModelAdapter):
+    """
+    A mock model adapter for testing and demonstration purposes.
+    
+    This adapter simulates responses without requiring an actual AI model.
+    """
+    
+    def __init__(self, model_id: str = "mock-model", capabilities: Dict[str, Any] = None):
+        """
+        Initialize a new MockModelAdapter.
+        
+        Args:
+            model_id: Identifier for this mock model.
+            capabilities: Dictionary of capabilities this mock model supports.
+        """
+        self.model_id = model_id
+        self._capabilities = capabilities or {
+            "text_generation": True,
+            "question_answering": True,
+            "content_evaluation": True,
+            "max_input_length": 1000,
+            "supports_streaming": False
+        }
+        
+    async def process(self, input_data: Dict[str, Any], context: Dict[str, Any] = None) -> Dict[str, Any]:
+        """
+        Process an input with the mock model.
+        
+        Args:
+            input_data: The input data to process.
+            context: Optional context information.
+            
+        Returns:
+            A mock response based on the input.
+        """
+        # Extract the input text or use a default
+        input_text = input_data.get("text", "")
+        
+        # Generate a mock response based on the input
+        if "question" in input_text.lower():
+            response = f"This is a mock answer to your question about {input_text.split('?')[0]}."
+        elif "explain" in input_text.lower():
+            topic = input_text.lower().split("explain")[1].strip()
+            response = f"Here's a mock explanation of {topic}. This would contain educational content in a real implementation."
+        else:
+            response = f"I've processed your input: '{input_text}'. This is a mock response that would be more relevant in a real implementation."
+            
+        # Include some educational metadata in the response
+        return {
+            "text": response,
+            "model_id": self.model_id,
+            "confidence": 0.85,
+            "educational_metadata": {
+                "complexity_level": "intermediate",
+                "topics": ["sample", "mock", "demonstration"],
+                "suggested_follow_ups": [
+                    "Tell me more about this topic",
+                    "Can you provide an example?",
+                    "What are the key concepts I should understand?"
+                ]
+            }
+        }
+    
+    def get_capabilities(self) -> Dict[str, Any]:
+        """
+        Get the capabilities of this mock model.
+        
+        Returns:
+            Dictionary describing the mock model's capabilities.
+        """
+        return self._capabilities
+
+
+class OpenAIAdapter(ModelAdapter):
+    """
+    Adapter for OpenAI models.
+    
+    This adapter provides an interface to OpenAI's models through their API.
+    Note: This is a placeholder implementation. In a real application, you would
+    need to implement the actual API calls to OpenAI.
+    """
+    
+    def __init__(self, model_name: str = "gpt-3.5-turbo", api_key: Optional[str] = None):
+        """
+        Initialize a new OpenAIAdapter.
+        
+        Args:
+            model_name: The name of the OpenAI model to use.
+            api_key: OpenAI API key. If None, will attempt to use environment variable.
+        """
+        self.model_name = model_name
+        self.api_key = api_key
+        # In a real implementation, you would initialize the OpenAI client here
+        
+    async def process(self, input_data: Dict[str, Any], context: Dict[str, Any] = None) -> Dict[str, Any]:
+        """
+        Process an input with an OpenAI model.
+        
+        Args:
+            input_data: The input data to process.
+            context: Optional context information.
+            
+        Returns:
+            The model's output.
+        """
+        # This is a placeholder. In a real implementation, you would:
+        # 1. Format the input and context for the OpenAI API
+        # 2. Make the API call
+        # 3. Process and return the response
+        
+        # Placeholder response
+        return {
+            "text": f"This is a placeholder response from {self.model_name}. In a real implementation, this would be the actual model output.",
+            "model": self.model_name,
+            "usage": {
+                "prompt_tokens": 10,
+                "completion_tokens": 20,
+                "total_tokens": 30
+            }
+        }
+    
+    def get_capabilities(self) -> Dict[str, Any]:
+        """
+        Get the capabilities of this OpenAI model.
+        
+        Returns:
+            Dictionary describing the model's capabilities.
+        """
+        # This would be more accurate in a real implementation
+        capabilities = {
+            "text_generation": True,
+            "question_answering": True,
+            "content_evaluation": True,
+            "supports_streaming": True
+        }
+        
+        # Different capabilities based on model
+        if "gpt-4" in self.model_name:
+            capabilities.update({
+                "max_input_length": 8000,
+                "reasoning_ability": "advanced"
+            })
+        else:
+            capabilities.update({
+                "max_input_length": 4000,
+                "reasoning_ability": "intermediate"
+            })
+            
+        return capabilities
+
+
+class HuggingFaceAdapter(ModelAdapter):
+    """
+    Adapter for Hugging Face models.
+    
+    This adapter provides an interface to models hosted on Hugging Face's model hub.
+    Note: This is a placeholder implementation. In a real application, you would
+    need to implement the actual API calls to Hugging Face.
+    """
+    
+    def __init__(self, model_id: str, api_key: Optional[str] = None):
+        """
+        Initialize a new HuggingFaceAdapter.
+        
+        Args:
+            model_id: The ID of the Hugging Face model to use.
+            api_key: Hugging Face API key. If None, will attempt to use environment variable.
+        """
+        self.model_id = model_id
+        self.api_key = api_key
+        # In a real implementation, you would initialize the Hugging Face client here
+        
+    async def process(self, input_data: Dict[str, Any], context: Dict[str, Any] = None) -> Dict[str, Any]:
+        """
+        Process an input with a Hugging Face model.
+        
+        Args:
+            input_data: The input data to process.
+            context: Optional context information.
+            
+        Returns:
+            The model's output.
+        """
+        # This is a placeholder. In a real implementation, you would:
+        # 1. Format the input and context for the Hugging Face API
+        # 2. Make the API call
+        # 3. Process and return the response
+        
+        # Placeholder response
+        return {
+            "text": f"This is a placeholder response from Hugging Face model {self.model_id}. In a real implementation, this would be the actual model output.",
+            "model": self.model_id
+        }
+    
+    def get_capabilities(self) -> Dict[str, Any]:
+        """
+        Get the capabilities of this Hugging Face model.
+        
+        Returns:
+            Dictionary describing the model's capabilities.
+        """
+        # This would be determined dynamically in a real implementation
+        return {
+            "text_generation": True,
+            "question_answering": True,
+            "content_evaluation": True,
+            "max_input_length": 2000,
+            "supports_streaming": False
+        }
+
+
+class ModelRegistry:
+    """
+    Registry for model adapters.
+    
+    This class manages the available model adapters and provides methods
+    for registering, retrieving, and listing them.
+    """
+    
+    def __init__(self):
+        """Initialize a new ModelRegistry."""
+        self.adapters: Dict[str, ModelAdapter] = {}
+        
+    def register_adapter(self, name: str, adapter: ModelAdapter) -> None:
+        """
+        Register a model adapter.
+        
+        Args:
+            name: Name to register the adapter under.
+            adapter: The ModelAdapter instance to register.
+        """
+        self.adapters[name] = adapter
+        
+    def get_adapter(self, name: str) -> Optional[ModelAdapter]:
+        """
+        Get a registered adapter by name.
+        
+        Args:
+            name: Name of the adapter to retrieve.
+            
+        Returns:
+            The ModelAdapter if found, None otherwise.
+        """
+        return self.adapters.get(name)
+    
+    def list_adapters(self) -> List[str]:
+        """
+        List all registered adapter names.
+        
+        Returns:
+            List of adapter names.
+        """
+        return list(self.adapters.keys())
+    
+    def get_adapter_capabilities(self, name: str) -> Optional[Dict[str, Any]]:
+        """
+        Get the capabilities of a registered adapter.
+        
+        Args:
+            name: Name of the adapter.
+            
+        Returns:
+            Dictionary of capabilities if the adapter exists, None otherwise.
+        """
+        adapter = self.get_adapter(name)
+        if adapter:
+            return adapter.get_capabilities()
+        return None

src/mcp_core/persistence.py

@@ -0,0 +1,505 @@
+"""
+MCP Core - State Persistence Layer
+
+This module provides functionality for persisting context state across sessions,
+allowing for long-term storage and retrieval of context data.
+"""
+
+import json
+import os
+import sqlite3
+from datetime import datetime
+from typing import Dict, List, Optional, Any, Union
+from abc import ABC, abstractmethod
+
+from .context import Context
+
+
+class PersistenceProvider(ABC):
+    """
+    Abstract base class for persistence providers.
+    
+    Persistence providers handle the storage and retrieval of context data,
+    allowing contexts to be persisted across sessions.
+    """
+    
+    @abstractmethod
+    async def save_context(self, context: Context) -> bool:
+        """
+        Save a context to persistent storage.
+        
+        Args:
+            context: The Context object to save.
+            
+        Returns:
+            True if the save was successful, False otherwise.
+        """
+        pass
+    
+    @abstractmethod
+    async def load_context(self, context_id: str) -> Optional[Context]:
+        """
+        Load a context from persistent storage.
+        
+        Args:
+            context_id: The ID of the context to load.
+            
+        Returns:
+            The loaded Context object if found, None otherwise.
+        """
+        pass
+    
+    @abstractmethod
+    async def delete_context(self, context_id: str) -> bool:
+        """
+        Delete a context from persistent storage.
+        
+        Args:
+            context_id: The ID of the context to delete.
+            
+        Returns:
+            True if the deletion was successful, False otherwise.
+        """
+        pass
+    
+    @abstractmethod
+    async def list_contexts(self, filter_criteria: Optional[Dict[str, Any]] = None) -> List[str]:
+        """
+        List context IDs in persistent storage, optionally filtered.
+        
+        Args:
+            filter_criteria: Optional criteria to filter contexts by.
+            
+        Returns:
+            List of context IDs matching the filter criteria.
+        """
+        pass
+
+
+class FileSystemProvider(PersistenceProvider):
+    """
+    File system-based persistence provider.
+    
+    This provider stores contexts as JSON files in the file system.
+    """
+    
+    def __init__(self, storage_dir: str = "./storage/contexts"):
+        """
+        Initialize a new FileSystemProvider.
+        
+        Args:
+            storage_dir: Directory to store context files in.
+        """
+        self.storage_dir = storage_dir
+        os.makedirs(storage_dir, exist_ok=True)
+        
+    def _get_context_path(self, context_id: str) -> str:
+        """
+        Get the file path for a context.
+        
+        Args:
+            context_id: The ID of the context.
+            
+        Returns:
+            The file path for the context.
+        """
+        return os.path.join(self.storage_dir, f"{context_id}.json")
+    
+    async def save_context(self, context: Context) -> bool:
+        """
+        Save a context to a JSON file.
+        
+        Args:
+            context: The Context object to save.
+            
+        Returns:
+            True if the save was successful, False otherwise.
+        """
+        try:
+            with open(self._get_context_path(context.context_id), 'w') as f:
+                json.dump(context.to_dict(), f, indent=2)
+            return True
+        except Exception as e:
+            print(f"Error saving context: {e}")
+            return False
+    
+    async def load_context(self, context_id: str) -> Optional[Context]:
+        """
+        Load a context from a JSON file.
+        
+        Args:
+            context_id: The ID of the context to load.
+            
+        Returns:
+            The loaded Context object if found, None otherwise.
+        """
+        try:
+            path = self._get_context_path(context_id)
+            if not os.path.exists(path):
+                return None
+                
+            with open(path, 'r') as f:
+                data = json.load(f)
+                
+            return Context.from_dict(data)
+        except Exception as e:
+            print(f"Error loading context: {e}")
+            return None
+    
+    async def delete_context(self, context_id: str) -> bool:
+        """
+        Delete a context JSON file.
+        
+        Args:
+            context_id: The ID of the context to delete.
+            
+        Returns:
+            True if the deletion was successful, False otherwise.
+        """
+        try:
+            path = self._get_context_path(context_id)
+            if os.path.exists(path):
+                os.remove(path)
+                return True
+            return False
+        except Exception as e:
+            print(f"Error deleting context: {e}")
+            return False
+    
+    async def list_contexts(self, filter_criteria: Optional[Dict[str, Any]] = None) -> List[str]:
+        """
+        List context IDs in the storage directory, optionally filtered.
+        
+        Args:
+            filter_criteria: Optional criteria to filter contexts by.
+            
+        Returns:
+            List of context IDs matching the filter criteria.
+        """
+        try:
+            context_ids = []
+            for filename in os.listdir(self.storage_dir):
+                if filename.endswith('.json'):
+                    context_id = filename[:-5]  # Remove .json extension
+                    
+                    # Apply filtering if criteria provided
+                    if filter_criteria:
+                        try:
+                            with open(self._get_context_path(context_id), 'r') as f:
+                                data = json.load(f)
+                                
+                            # Check if context matches all filter criteria
+                            matches = True
+                            for key, value in filter_criteria.items():
+                                # Handle nested keys with dot notation
+                                if '.' in key:
+                                    parts = key.split('.')
+                                    current = data
+                                    for part in parts:
+                                        if part not in current:
+                                            matches = False
+                                            break
+                                        current = current[part]
+                                    if matches and current != value:
+                                        matches = False
+                                elif key not in data or data[key] != value:
+                                    matches = False
+                                    
+                            if matches:
+                                context_ids.append(context_id)
+                        except:
+                            # Skip contexts that can't be loaded or don't match
+                            continue
+                    else:
+                        context_ids.append(context_id)
+                        
+            return context_ids
+        except Exception as e:
+            print(f"Error listing contexts: {e}")
+            return []
+
+
+class SQLiteProvider(PersistenceProvider):
+    """
+    SQLite-based persistence provider.
+    
+    This provider stores contexts in an SQLite database.
+    """
+    
+    def __init__(self, db_path: str = "./storage/contexts.db"):
+        """
+        Initialize a new SQLiteProvider.
+        
+        Args:
+            db_path: Path to the SQLite database file.
+        """
+        os.makedirs(os.path.dirname(db_path), exist_ok=True)
+        self.db_path = db_path
+        self._init_db()
+        
+    def _init_db(self):
+        """Initialize the database schema if it doesn't exist."""
+        conn = sqlite3.connect(self.db_path)
+        cursor = conn.cursor()
+        
+        # Create contexts table
+        cursor.execute('''
+        CREATE TABLE IF NOT EXISTS contexts (
+            context_id TEXT PRIMARY KEY,
+            metadata TEXT,
+            state TEXT,
+            history TEXT,
+            created_at TEXT,
+            updated_at TEXT
+        )
+        ''')
+        
+        conn.commit()
+        conn.close()
+        
+    async def save_context(self, context: Context) -> bool:
+        """
+        Save a context to the SQLite database.
+        
+        Args:
+            context: The Context object to save.
+            
+        Returns:
+            True if the save was successful, False otherwise.
+        """
+        try:
+            conn = sqlite3.connect(self.db_path)
+            cursor = conn.cursor()
+            
+            # Convert complex objects to JSON strings
+            context_data = context.to_dict()
+            metadata = json.dumps(context_data.get("metadata", {}))
+            state = json.dumps(context_data.get("state", {}))
+            history = json.dumps(context_data.get("history", []))
+            
+            # Check if context already exists
+            cursor.execute("SELECT 1 FROM contexts WHERE context_id = ?", (context.context_id,))
+            exists = cursor.fetchone() is not None
+            
+            if exists:
+                # Update existing context
+                cursor.execute('''
+                UPDATE contexts
+                SET metadata = ?, state = ?, history = ?, updated_at = ?
+                WHERE context_id = ?
+                ''', (metadata, state, history, context.updated_at.isoformat(), context.context_id))
+            else:
+                # Insert new context
+                cursor.execute('''
+                INSERT INTO contexts (context_id, metadata, state, history, created_at, updated_at)
+                VALUES (?, ?, ?, ?, ?, ?)
+                ''', (
+                    context.context_id,
+                    metadata,
+                    state,
+                    history,
+                    context.created_at.isoformat(),
+                    context.updated_at.isoformat()
+                ))
+                
+            conn.commit()
+            conn.close()
+            return True
+        except Exception as e:
+            print(f"Error saving context to SQLite: {e}")
+            return False
+    
+    async def load_context(self, context_id: str) -> Optional[Context]:
+        """
+        Load a context from the SQLite database.
+        
+        Args:
+            context_id: The ID of the context to load.
+            
+        Returns:
+            The loaded Context object if found, None otherwise.
+        """
+        try:
+            conn = sqlite3.connect(self.db_path)
+            cursor = conn.cursor()
+            
+            cursor.execute('''
+            SELECT context_id, metadata, state, history, created_at, updated_at
+            FROM contexts
+            WHERE context_id = ?
+            ''', (context_id,))
+            
+            row = cursor.fetchone()
+            conn.close()
+            
+            if not row:
+                return None
+                
+            # Reconstruct context from database row
+            context_data = {
+                "context_id": row[0],
+                "metadata": json.loads(row[1]),
+                "state": json.loads(row[2]),
+                "history": json.loads(row[3]),
+                "created_at": row[4],
+                "updated_at": row[5]
+            }
+            
+            return Context.from_dict(context_data)
+        except Exception as e:
+            print(f"Error loading context from SQLite: {e}")
+            return None
+    
+    async def delete_context(self, context_id: str) -> bool:
+        """
+        Delete a context from the SQLite database.
+        
+        Args:
+            context_id: The ID of the context to delete.
+            
+        Returns:
+            True if the deletion was successful, False otherwise.
+        """
+        try:
+            conn = sqlite3.connect(self.db_path)
+            cursor = conn.cursor()
+            
+            cursor.execute("DELETE FROM contexts WHERE context_id = ?", (context_id,))
+            deleted = cursor.rowcount > 0
+            
+            conn.commit()
+            conn.close()
+            
+            return deleted
+        except Exception as e:
+            print(f"Error deleting context from SQLite: {e}")
+            return False
+    
+    async def list_contexts(self, filter_criteria: Optional[Dict[str, Any]] = None) -> List[str]:
+        """
+        List context IDs in the SQLite database, optionally filtered.
+        
+        Args:
+            filter_criteria: Optional criteria to filter contexts by.
+            
+        Returns:
+            List of context IDs matching the filter criteria.
+        """
+        try:
+            conn = sqlite3.connect(self.db_path)
+            cursor = conn.cursor()
+            
+            if not filter_criteria:
+                # Simple case: no filtering
+                cursor.execute("SELECT context_id FROM contexts")
+                context_ids = [row[0] for row in cursor.fetchall()]
+            else:
+                # Complex case: need to load and filter each context
+                cursor.execute("SELECT context_id, metadata, state FROM contexts")
+                rows = cursor.fetchall()
+                
+                context_ids = []
+                for row in rows:
+                    context_id = row[0]
+                    metadata = json.loads(row[1])
+                    state = json.loads(row[2])
+                    
+                    # Check if context matches all filter criteria
+                    matches = True
+                    for key, value in filter_criteria.items():
+                        if key.startswith("metadata."):
+                            # Filter on metadata field
+                            field = key[9:]  # Remove "metadata." prefix
+                            if field not in metadata or metadata[field] != value:
+                                matches = False
+                                break
+                        elif key.startswith("state."):
+                            # Filter on state field
+                            field = key[6:]  # Remove "state." prefix
+                            if field not in state or state[field] != value:
+                                matches = False
+                                break
+                                
+                    if matches:
+                        context_ids.append(context_id)
+            
+            conn.close()
+            return context_ids
+        except Exception as e:
+            print(f"Error listing contexts from SQLite: {e}")
+            return []
+
+
+class PersistenceManager:
+    """
+    Manages context persistence operations.
+    
+    This class provides a unified interface for working with different
+    persistence providers.
+    """
+    
+    def __init__(self, provider: PersistenceProvider):
+        """
+        Initialize a new PersistenceManager.
+        
+        Args:
+            provider: The persistence provider to use.
+        """
+        self.provider = provider
+        
+    async def save_context(self, context: Context) -> bool:
+        """
+        Save a context using the configured provider.
+        
+        Args:
+            context: The Context object to save.
+            
+        Returns:
+            True if the save was successful, False otherwise.
+        """
+        return await self.provider.save_context(context)
+    
+    async def load_context(self, context_id: str) -> Optional[Context]:
+        """
+        Load a context using the configured provider.
+        
+        Args:
+            context_id: The ID of the context to load.
+            
+        Returns:
+            The loaded Context object if found, None otherwise.
+        """
+        return await self.provider.load_context(context_id)
+    
+    async def delete_context(self, context_id: str) -> bool:
+        """
+        Delete a context using the configured provider.
+        
+        Args:
+            context_id: The ID of the context to delete.
+            
+        Returns:
+            True if the deletion was successful, False otherwise.
+        """
+        return await self.provider.delete_context(context_id)
+    
+    async def list_contexts(self, filter_criteria: Optional[Dict[str, Any]] = None) -> List[str]:
+        """
+        List context IDs using the configured provider, optionally filtered.
+        
+        Args:
+            filter_criteria: Optional criteria to filter contexts by.
+            
+        Returns:
+            List of context IDs matching the filter criteria.
+        """
+        return await self.provider.list_contexts(filter_criteria)
+    
+    def change_provider(self, provider: PersistenceProvider) -> None:
+        """
+        Change the persistence provider.
+        
+        Args:
+            provider: The new persistence provider to use.
+        """
+        self.provider = provider

src/mcp_core/processor.py

@@ -0,0 +1,184 @@
+"""
+MCP Core - Interaction Processor
+
+This module provides the core functionality for processing interactions
+between users and models through the Model Context Protocol.
+"""
+
+from typing import Dict, Any, Optional, List, Union
+import asyncio
+
+from .context import Context, ContextManager
+from .model_adapters import ModelAdapter, ModelRegistry
+from .protocol import MCPRequest, MCPResponse, InteractionType
+
+
+class InteractionProcessor:
+    """
+    Processes interactions between users and models.
+    
+    This class handles the flow of interactions through the MCP system,
+    managing context, routing to appropriate models, and formatting responses.
+    """
+    
+    def __init__(
+        self, 
+        context_manager: ContextManager,
+        model_registry: ModelRegistry
+    ):
+        """
+        Initialize a new InteractionProcessor.
+        
+        Args:
+            context_manager: The ContextManager to use for context operations.
+            model_registry: The ModelRegistry to use for model operations.
+        """
+        self.context_manager = context_manager
+        self.model_registry = model_registry
+        
+    async def process_interaction(
+        self, 
+        request: MCPRequest,
+        model_name: str
+    ) -> MCPResponse:
+        """
+        Process an interaction request.
+        
+        Args:
+            request: The MCPRequest to process.
+            model_name: Name of the model adapter to use.
+            
+        Returns:
+            An MCPResponse containing the model's response.
+            
+        Raises:
+            ValueError: If the context ID is invalid or the model is not found.
+        """
+        # Get or create context
+        context_id = request.context_id
+        context = None
+        
+        if context_id:
+            # Use existing context
+            context = self.context_manager.get_context(context_id)
+            if not context:
+                raise ValueError(f"Context with ID {context_id} not found")
+        else:
+            # Create new context
+            context = self.context_manager.create_context(
+                metadata={"interaction_type": request.interaction_type}
+            )
+            context_id = context.context_id
+            
+        # Get model adapter
+        model_adapter = self.model_registry.get_adapter(model_name)
+        if not model_adapter:
+            raise ValueError(f"Model adapter '{model_name}' not found")
+            
+        # Process the request with the model
+        model_input = {
+            "text": request.content.get("text", ""),
+            "interaction_type": request.interaction_type,
+            "format": request.format,
+            **request.metadata
+        }
+        
+        # Include context state in model input
+        model_context = {
+            "state": context.state,
+            "history": context.get_history(5)  # Last 5 interactions
+        }
+        
+        # Process with model
+        model_output = await model_adapter.process(model_input, model_context)
+        
+        # Update context with this interaction
+        context.add_interaction(request.dict(), model_output)
+        
+        # Extract educational metadata if available
+        educational_metadata = model_output.get("educational_metadata", {})
+        if educational_metadata:
+            # Update context state with educational information
+            context.update_state({
+                "educational": {
+                    "last_topics": educational_metadata.get("topics", []),
+                    "complexity_level": educational_metadata.get("complexity_level", ""),
+                    "suggested_follow_ups": educational_metadata.get("suggested_follow_ups", [])
+                }
+            })
+        
+        # Create response
+        response = MCPResponse(
+            context_id=context_id,
+            interaction_type=request.interaction_type,
+            content={
+                "text": model_output.get("text", ""),
+                "educational_metadata": educational_metadata
+            },
+            format=request.format,
+            metadata=request.metadata,
+            model_info={
+                "model_id": model_output.get("model_id", model_name),
+                "confidence": model_output.get("confidence", 1.0)
+            }
+        )
+        
+        return response
+
+
+class BatchProcessor:
+    """
+    Processes batches of interactions.
+    
+    This class provides functionality for processing multiple interactions
+    in parallel or sequence.
+    """
+    
+    def __init__(self, interaction_processor: InteractionProcessor):
+        """
+        Initialize a new BatchProcessor.
+        
+        Args:
+            interaction_processor: The InteractionProcessor to use.
+        """
+        self.interaction_processor = interaction_processor
+        
+    async def process_batch(
+        self, 
+        requests: List[Dict[str, Any]],
+        model_name: str,
+        parallel: bool = True
+    ) -> List[Dict[str, Any]]:
+        """
+        Process a batch of interaction requests.
+        
+        Args:
+            requests: List of request dictionaries.
+            model_name: Name of the model adapter to use.
+            parallel: Whether to process requests in parallel.
+            
+        Returns:
+            List of response dictionaries.
+        """
+        if parallel:
+            # Process requests in parallel
+            tasks = [
+                self.interaction_processor.process_interaction(
+                    MCPRequest(**request),
+                    model_name
+                )
+                for request in requests
+            ]
+            responses = await asyncio.gather(*tasks)
+        else:
+            # Process requests sequentially
+            responses = []
+            for request in requests:
+                response = await self.interaction_processor.process_interaction(
+                    MCPRequest(**request),
+                    model_name
+                )
+                responses.append(response)
+                
+        # Convert responses to dictionaries
+        return [response.dict() for response in responses]

src/mcp_core/protocol.py

@@ -0,0 +1,158 @@
+from enum import Enum
+from typing import Dict, List, Any, Optional, Union, Literal
+from pydantic import BaseModel, Field
+
+
+class InteractionType(str, Enum):
+    TEXT = "text"
+    QUESTION = "question"
+    ASSESSMENT = "assessment"
+    EXPLANATION = "explanation"
+    FEEDBACK = "feedback"
+    SUMMARY = "summary"
+
+
+class ContentFormat(str, Enum):
+    TEXT = "text"
+    MARKDOWN = "markdown"
+    HTML = "html"
+    JSON = "json"
+
+
+class EducationalLevel(str, Enum):
+    ELEMENTARY = "elementary"
+    MIDDLE_SCHOOL = "middle_school"
+    HIGH_SCHOOL = "high_school"
+    UNDERGRADUATE = "undergraduate"
+    GRADUATE = "graduate"
+    PROFESSIONAL = "professional"
+
+
+class MCPRequest(BaseModel):
+    context_id: Optional[str] = Field(None)
+    interaction_type: InteractionType = Field(...)
+    content: Dict[str, Any] = Field(...)
+    format: ContentFormat = Field(ContentFormat.TEXT)
+    metadata: Dict[str, Any] = Field(default_factory=dict)
+
+
+class MCPResponse(BaseModel):
+    context_id: str = Field(...)
+    interaction_type: InteractionType = Field(...)
+    content: Dict[str, Any] = Field(...)
+    format: ContentFormat = Field(...)
+    metadata: Dict[str, Any] = Field(default_factory=dict)
+    model_info: Dict[str, Any] = Field(default_factory=dict)
+
+
+class TextRequest(MCPRequest):
+    interaction_type: Literal[InteractionType.TEXT] = Field(InteractionType.TEXT)
+    content: Dict[str, Any] = Field(...)
+
+
+class TextResponse(MCPResponse):
+    interaction_type: Literal[InteractionType.TEXT] = Field(InteractionType.TEXT)
+    content: Dict[str, Any] = Field(...)
+
+
+class QuestionRequest(MCPRequest):
+    interaction_type: Literal[InteractionType.QUESTION] = Field(InteractionType.QUESTION)
+    content: Dict[str, Any] = Field(...)
+
+
+class QuestionResponse(MCPResponse):
+    interaction_type: Literal[InteractionType.QUESTION] = Field(InteractionType.QUESTION)
+    content: Dict[str, Any] = Field(...)
+
+
+class AssessmentRequest(MCPRequest):
+    interaction_type: Literal[InteractionType.ASSESSMENT] = Field(InteractionType.ASSESSMENT)
+    content: Dict[str, Any] = Field(...)
+
+
+class AssessmentResponse(MCPResponse):
+    interaction_type: Literal[InteractionType.ASSESSMENT] = Field(InteractionType.ASSESSMENT)
+    content: Dict[str, Any] = Field(...)
+
+
+class ExplanationRequest(MCPRequest):
+    interaction_type: Literal[InteractionType.EXPLANATION] = Field(InteractionType.EXPLANATION)
+    content: Dict[str, Any] = Field(...)
+
+
+class ExplanationResponse(MCPResponse):
+    interaction_type: Literal[InteractionType.EXPLANATION] = Field(InteractionType.EXPLANATION)
+    content: Dict[str, Any] = Field(...)
+
+
+class FeedbackRequest(MCPRequest):
+    interaction_type: Literal[InteractionType.FEEDBACK] = Field(InteractionType.FEEDBACK)
+    content: Dict[str, Any] = Field(...)
+
+
+class FeedbackResponse(MCPResponse):
+    interaction_type: Literal[InteractionType.FEEDBACK] = Field(InteractionType.FEEDBACK)
+    content: Dict[str, Any] = Field(...)
+
+
+class SummaryRequest(MCPRequest):
+    interaction_type: Literal[InteractionType.SUMMARY] = Field(InteractionType.SUMMARY)
+    content: Dict[str, Any] = Field(...)
+
+
+class SummaryResponse(MCPResponse):
+    interaction_type: Literal[InteractionType.SUMMARY] = Field(InteractionType.SUMMARY)
+    content: Dict[str, Any] = Field(...)
+
+
+class LearningObjective(BaseModel):
+    id: str = Field(...)
+    description: str = Field(...)
+    taxonomy_level: str = Field(...)
+    subject_area: str = Field(...)
+    prerequisites: List[str] = Field(default_factory=list)
+
+
+class StudentProfile(BaseModel):
+    id: str = Field(...)
+    name: str = Field(...)
+    educational_level: EducationalLevel = Field(...)
+    learning_style: str = Field(None)
+    interests: List[str] = Field(default_factory=list)
+    strengths: List[str] = Field(default_factory=list)
+    areas_for_improvement: List[str] = Field(default_factory=list)
+    completed_objectives: List[str] = Field(default_factory=list)
+    current_objectives: List[str] = Field(default_factory=list)
+
+
+class ContentAdaptationRequest(MCPRequest):
+    interaction_type: Literal[InteractionType.TEXT] = Field(InteractionType.TEXT)
+    content: Dict[str, Any] = Field(...)
+    student_profile: StudentProfile = Field(...)
+    learning_objectives: List[LearningObjective] = Field(...)
+
+
+class ContentAdaptationResponse(MCPResponse):
+    interaction_type: Literal[InteractionType.TEXT] = Field(InteractionType.TEXT)
+    content: Dict[str, Any] = Field(...)
+    adaptations_applied: List[str] = Field(...)
+    recommended_activities: List[Dict[str, Any]] = Field(default_factory=list)
+
+
+MCP_VERSION = "1.0.0"
+MCP_SPEC_URL = "https://example.com/mcp-specification"
+
+MCP_CAPABILITIES = {
+    "version": MCP_VERSION,
+    "supported_interaction_types": [e.value for e in InteractionType],
+    "supported_content_formats": [e.value for e in ContentFormat],
+    "supported_educational_levels": [e.value for e in EducationalLevel],
+    "features": {
+        "context_management": True,
+        "state_persistence": True,
+        "content_adaptation": True,
+        "assessment": True,
+        "feedback": True,
+        "learning_path_generation": True
+    }
+}

src/static/index.html

@@ -0,0 +1,483 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>MCP EdTech Demo</title>
+    <link href="https://cdn.jsdelivr.net/npm/bootstrap@5.3.0-alpha1/dist/css/bootstrap.min.css" rel="stylesheet">
+    <style>
+        body {
+            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+            padding-top: 20px;
+            background-color: #f8f9fa;
+        }
+        .navbar {
+            background-color: #4a6fa5 !important;
+            box-shadow: 0 2px 4px rgba(0,0,0,0.1);
+        }
+        .navbar-brand {
+            font-weight: bold;
+            color: white !important;
+        }
+        .nav-link {
+            color: rgba(255,255,255,0.85) !important;
+        }
+        .nav-link:hover {
+            color: white !important;
+        }
+        .card {
+            border-radius: 10px;
+            box-shadow: 0 4px 6px rgba(0,0,0,0.1);
+            margin-bottom: 20px;
+            transition: transform 0.3s;
+        }
+        .card:hover {
+            transform: translateY(-5px);
+        }
+        .card-header {
+            background-color: #4a6fa5;
+            color: white;
+            font-weight: bold;
+            border-radius: 10px 10px 0 0 !important;
+        }
+        .btn-primary {
+            background-color: #4a6fa5;
+            border-color: #4a6fa5;
+        }
+        .btn-primary:hover {
+            background-color: #3a5a8f;
+            border-color: #3a5a8f;
+        }
+        .api-url {
+            font-family: monospace;
+            background-color: #f1f1f1;
+            padding: 5px;
+            border-radius: 4px;
+        }
+        .response-area {
+            background-color: #f8f9fa;
+            border: 1px solid #dee2e6;
+            border-radius: 5px;
+            padding: 15px;
+            max-height: 300px;
+            overflow-y: auto;
+            font-family: monospace;
+        }
+        .footer {
+            margin-top: 50px;
+            padding: 20px 0;
+            background-color: #343a40;
+            color: white;
+        }
+        #loading {
+            display: none;
+        }
+        .spinner-border {
+            width: 1rem;
+            height: 1rem;
+        }
+    </style>
+</head>
+<body>
+    <nav class="navbar navbar-expand-lg navbar-dark bg-dark mb-4">
+        <div class="container">
+            <a class="navbar-brand" href="#">MCP EdTech</a>
+            <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbarNav">
+                <span class="navbar-toggler-icon"></span>
+            </button>
+            <div class="collapse navbar-collapse" id="navbarNav">
+                <ul class="navbar-nav">
+                    <li class="nav-item">
+                        <a class="nav-link active" href="#home">Home</a>
+                    </li>
+                    <li class="nav-item">
+                        <a class="nav-link" href="#api-demo">API Demo</a>
+                    </li>
+                    <li class="nav-item">
+                        <a class="nav-link" href="#documentation">Documentation</a>
+                    </li>
+                </ul>
+            </div>
+        </div>
+    </nav>
+
+    <div class="container" id="home">
+        <div class="row mb-4">
+            <div class="col-12">
+                <div class="card">
+                    <div class="card-header">
+                        Model Context Protocol (MCP) for EdTech
+                    </div>
+                    <div class="card-body">
+                        <h5 class="card-title">Welcome to the MCP EdTech Demo</h5>
+                        <p class="card-text">
+                            This demo showcases the Model Context Protocol (MCP) implementation for educational technology applications.
+                            MCP provides a standardized way for EdTech applications to interact with various AI models while maintaining
+                            context and state across interactions.
+                        </p>
+                        <p>
+                            Key features of this implementation:
+                        </p>
+                        <ul>
+                            <li>Context management for stateful conversations</li>
+                            <li>Student profile management</li>
+                            <li>Learning progress tracking</li>
+                            <li>Content adaptation based on student profiles</li>
+                            <li>Assessment and feedback systems</li>
+                        </ul>
+                    </div>
+                </div>
+            </div>
+        </div>
+
+        <div class="row mb-4" id="api-demo">
+            <div class="col-12">
+                <div class="card">
+                    <div class="card-header">
+                        API Demo
+                    </div>
+                    <div class="card-body">
+                        <h5 class="card-title">Try the MCP API</h5>
+                        
+                        <div class="mb-4">
+                            <h6>1. Create a Context</h6>
+                            <p>First, let's create a new context for our interaction:</p>
+                            <div class="mb-3">
+                                <button id="createContextBtn" class="btn btn-primary">Create Context</button>
+                                <span id="loading-context" class="ms-2" style="display: none;">
+                                    <span class="spinner-border spinner-border-sm"></span> Processing...
+                                </span>
+                            </div>
+                            <div class="response-area" id="contextResponse">
+                                <!-- Context response will appear here -->
+                            </div>
+                        </div>
+                        
+                        <div class="mb-4">
+                            <h6>2. Process an Interaction</h6>
+                            <p>Now, let's process an interaction using the context we created:</p>
+                            <div class="mb-3">
+                                <label for="interactionText" class="form-label">Enter your question or prompt:</label>
+                                <input type="text" class="form-control" id="interactionText" 
+                                    placeholder="e.g., Explain the concept of photosynthesis">
+                            </div>
+                            <div class="mb-3">
+                                <button id="interactBtn" class="btn btn-primary">Process Interaction</button>
+                                <span id="loading-interaction" class="ms-2" style="display: none;">
+                                    <span class="spinner-border spinner-border-sm"></span> Processing...
+                                </span>
+                            </div>
+                            <div class="response-area" id="interactionResponse">
+                                <!-- Interaction response will appear here -->
+                            </div>
+                        </div>
+                        
+                        <div class="mb-4">
+                            <h6>3. Create a Student Profile</h6>
+                            <p>Let's create a student profile:</p>
+                            <div class="mb-3">
+                                <label for="studentName" class="form-label">Student Name:</label>
+                                <input type="text" class="form-control" id="studentName" placeholder="John Doe">
+                            </div>
+                            <div class="mb-3">
+                                <label for="educationalLevel" class="form-label">Educational Level:</label>
+                                <select class="form-select" id="educationalLevel">
+                                    <option value="elementary">Elementary</option>
+                                    <option value="middle_school">Middle School</option>
+                                    <option value="high_school">High School</option>
+                                    <option value="undergraduate">Undergraduate</option>
+                                    <option value="graduate">Graduate</option>
+                                    <option value="professional">Professional</option>
+                                </select>
+                            </div>
+                            <div class="mb-3">
+                                <button id="createStudentBtn" class="btn btn-primary">Create Student Profile</button>
+                                <span id="loading-student" class="ms-2" style="display: none;">
+                                    <span class="spinner-border spinner-border-sm"></span> Processing...
+                                </span>
+                            </div>
+                            <div class="response-area" id="studentResponse">
+                                <!-- Student profile response will appear here -->
+                            </div>
+                        </div>
+                        
+                        <div class="mb-4">
+                            <h6>4. Adapt Content for Student</h6>
+                            <p>Now, let's adapt some content for the student:</p>
+                            <div class="mb-3">
+                                <label for="contentText" class="form-label">Content to adapt:</label>
+                                <textarea class="form-control" id="contentText" rows="3" 
+                                    placeholder="The process of photosynthesis involves the conversion of light energy into chemical energy that can be used by plants and other organisms."></textarea>
+                            </div>
+                            <div class="mb-3">
+                                <button id="adaptContentBtn" class="btn btn-primary">Adapt Content</button>
+                                <span id="loading-content" class="ms-2" style="display: none;">
+                                    <span class="spinner-border spinner-border-sm"></span> Processing...
+                                </span>
+                            </div>
+                            <div class="response-area" id="contentResponse">
+                                <!-- Content adaptation response will appear here -->
+                            </div>
+                        </div>
+                    </div>
+                </div>
+            </div>
+        </div>
+
+        <div class="row mb-4" id="documentation">
+            <div class="col-12">
+                <div class="card">
+                    <div class="card-header">
+                        API Documentation
+                    </div>
+                    <div class="card-body">
+                        <h5 class="card-title">Available Endpoints</h5>
+                        
+                        <div class="mb-3">
+                            <h6>Context Management</h6>
+                            <ul>
+                                <li><span class="api-url">POST /api/v1/context/create</span> - Create a new context</li>
+                                <li><span class="api-url">GET /api/v1/context/{context_id}</span> - Get context information</li>
+                                <li><span class="api-url">PUT /api/v1/context/{context_id}</span> - Update context</li>
+                                <li><span class="api-url">DELETE /api/v1/context/{context_id}</span> - Delete context</li>
+                            </ul>
+                        </div>
+                        
+                        <div class="mb-3">
+                            <h6>Interaction</h6>
+                            <ul>
+                                <li><span class="api-url">POST /api/v1/interact</span> - Process an interaction</li>
+                            </ul>
+                        </div>
+                        
+                        <div class="mb-3">
+                            <h6>Student Profiles</h6>
+                            <ul>
+                                <li><span class="api-url">POST /api/v1/students</span> - Create student profile</li>
+                                <li><span class="api-url">GET /api/v1/students/{student_id}</span> - Get student information</li>
+                                <li><span class="api-url">PUT /api/v1/students/{student_id}</span> - Update student information</li>
+                            </ul>
+                        </div>
+                        
+                        <div class="mb-3">
+                            <h6>Progress Tracking</h6>
+                            <ul>
+                                <li><span class="api-url">GET /api/v1/students/{student_id}/progress</span> - Get learning progress</li>
+                                <li><span class="api-url">POST /api/v1/assessments</span> - Create assessment</li>
+                                <li><span class="api-url">GET /api/v1/students/{student_id}/assessments</span> - List student assessments</li>
+                            </ul>
+                        </div>
+                        
+                        <div class="mb-3">
+                            <h6>Content Adaptation</h6>
+                            <ul>
+                                <li><span class="api-url">POST /api/v1/content/adapt</span> - Adapt content for a student</li>
+                            </ul>
+                        </div>
+                        
+                        <div class="mb-3">
+                            <h6>Learning Paths</h6>
+                            <ul>
+                                <li><span class="api-url">GET /api/v1/learning-paths/{student_id}</span> - Get personalized learning path</li>
+                            </ul>
+                        </div>
+                        
+                        <div class="mb-3">
+                            <h6>Models</h6>
+                            <ul>
+                                <li><span class="api-url">GET /api/v1/models</span> - List available models</li>
+                                <li><span class="api-url">GET /api/v1/models/{model_name}/capabilities</span> - Get model capabilities</li>
+                            </ul>
+                        </div>
+                        
+                        <p class="mt-4">
+                            For complete API documentation, visit the <a href="/docs" target="_blank">Swagger UI</a> or 
+                            <a href="/redoc" target="_blank">ReDoc</a> pages.
+                        </p>
+                    </div>
+                </div>
+            </div>
+        </div>
+    </div>
+
+    <footer class="footer">
+        <div class="container">
+            <div class="row">
+                <div class="col-md-6">
+                    <h5>MCP EdTech Project</h5>
+                    <p>An open-source implementation of the Model Context Protocol for educational technology applications.</p>
+                </div>
+                <div class="col-md-6 text-md-end">
+                    <p>© 2025 MCP EdTech Project</p>
+                    <p>Licensed under MIT License</p>
+                </div>
+            </div>
+        </div>
+    </footer>
+
+    <script src="https://cdn.jsdelivr.net/npm/bootstrap@5.3.0-alpha1/dist/js/bootstrap.bundle.min.js"></script>
+    <script>
+        // Store context and student IDs
+        let currentContextId = null;
+        let currentStudentId = null;
+
+        // Function to format JSON responses
+        function formatJSON(json) {
+            return JSON.stringify(json, null, 2);
+        }
+
+        // Create Context
+        document.getElementById('createContextBtn').addEventListener('click', async () => {
+            const loadingElement = document.getElementById('loading-context');
+            loadingElement.style.display = 'inline';
+            
+            try {
+                const response = await fetch('/api/v1/context/create', {
+                    method: 'POST',
+                    headers: {
+                        'Content-Type': 'application/json'
+                    },
+                    body: JSON.stringify({
+                        metadata: {
+                            source: 'demo-ui',
+                            created_by: 'demo-user'
+                        }
+                    })
+                });
+                
+                const data = await response.json();
+                currentContextId = data.context_id;
+                
+                document.getElementById('contextResponse').innerText = formatJSON(data);
+            } catch (error) {
+                document.getElementById('contextResponse').innerText = `Error: ${error.message}`;
+            } finally {
+                loadingElement.style.display = 'none';
+            }
+        });
+
+        // Process Interaction
+        document.getElementById('interactBtn').addEventListener('click', async () => {
+            if (!currentContextId) {
+                alert('Please create a context first!');
+                return;
+            }
+            
+            const interactionText = document.getElementById('interactionText').value;
+            if (!interactionText) {
+                alert('Please enter a question or prompt!');
+                return;
+            }
+            
+            const loadingElement = document.getElementById('loading-interaction');
+            loadingElement.style.display = 'inline';
+            
+            try {
+                const response = await fetch('/api/v1/interact', {
+                    method: 'POST',
+                    headers: {
+                        'Content-Type': 'application/json'
+                    },
+                    body: JSON.stringify({
+                        context_id: currentContextId,
+                        interaction_type: 'text',
+                        content: {
+                            text: interactionText
+                        },
+                        format: 'text',
+                        model_name: 'mock'
+                    })
+                });
+                
+                const data = await response.json();
+                document.getElementById('interactionResponse').innerText = formatJSON(data);
+            } catch (error) {
+                document.getElementById('interactionResponse').innerText = `Error: ${error.message}`;
+            } finally {
+                loadingElement.style.display = 'none';
+            }
+        });
+
+        // Create Student Profile
+        document.getElementById('createStudentBtn').addEventListener('click', async () => {
+            const studentName = document.getElementById('studentName').value;
+            if (!studentName) {
+                alert('Please enter a student name!');
+                return;
+            }
+            
+            const educationalLevel = document.getElementById('educationalLevel').value;
+            
+            const loadingElement = document.getElementById('loading-student');
+            loadingElement.style.display = 'inline';
+            
+            try {
+                const response = await fetch('/api/v1/students', {
+                    method: 'POST',
+                    headers: {
+                        'Content-Type': 'application/json'
+                    },
+                    body: JSON.stringify({
+                        name: studentName,
+                        educational_level: educationalLevel,
+                        learning_style: 'visual',
+                        interests: ['science', 'technology', 'art'],
+                        strengths: ['problem-solving', 'creativity'],
+                        areas_for_improvement: ['time-management']
+                    })
+                });
+                
+                const data = await response.json();
+                currentStudentId = data.id;
+                
+                document.getElementById('studentResponse').innerText = formatJSON(data);
+            } catch (error) {
+                document.getElementById('studentResponse').innerText = `Error: ${error.message}`;
+            } finally {
+                loadingElement.style.display = 'none';
+            }
+        });
+
+        // Adapt Content
+        document.getElementById('adaptContentBtn').addEventListener('click', async () => {
+            if (!currentStudentId) {
+                alert('Please create a student profile first!');
+                return;
+            }
+            
+            const contentText = document.getElementById('contentText').value;
+            if (!contentText) {
+                alert('Please enter content to adapt!');
+                return;
+            }
+            
+            const loadingElement = document.getElementById('loading-content');
+            loadingElement.style.display = 'inline';
+            
+            try {
+                const response = await fetch('/api/v1/content/adapt', {
+                    method: 'POST',
+                    headers: {
+                        'Content-Type': 'application/json'
+                    },
+                    body: JSON.stringify({
+                        content: {
+                            text: contentText
+                        },
+                        student_id: currentStudentId,
+                        learning_objectives: ['obj-1', 'obj-2'],
+                        content_format: 'text'
+                    })
+                });
+                
+                const data = await response.json();
+                document.getElementById('contentResponse').innerText = formatJSON(data);
+            } catch (error) {
+                document.getElementById('contentResponse').innerText = `Error: ${error.message}`;
+            } finally {
+                loadingElement.style.display = 'none';
+            }
+        });
+    </script>
+</body>
+</html>

static/index.html

@@ -0,0 +1,411 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>MCP EdTech Demo</title>
+    <style>
+        :root {
+            --primary-color: #4a6fa5;
+            --secondary-color: #6c757d;
+            --accent-color: #28a745;
+            --light-bg: #f8f9fa;
+            --dark-bg: #343a40;
+            --text-color: #333;
+        }
+        
+        body {
+            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+            line-height: 1.6;
+            color: var(--text-color);
+            margin: 0;
+            padding: 0;
+            background-color: #f5f7fa;
+        }
+        
+        .navbar {
+            background-color: var(--primary-color);
+            color: white;
+            padding: 1rem;
+            display: flex;
+            justify-content: space-between;
+            align-items: center;
+        }
+        
+        .navbar-brand {
+            font-size: 1.5rem;
+            font-weight: bold;
+            color: white;
+            text-decoration: none;
+        }
+        
+        .navbar-nav {
+            display: flex;
+            list-style: none;
+            margin: 0;
+            padding: 0;
+        }
+        
+        .nav-item {
+            margin-left: 1.5rem;
+        }
+        
+        .nav-link {
+            color: white;
+            text-decoration: none;
+            transition: color 0.3s;
+        }
+        
+        .nav-link:hover {
+            color: #e0e0e0;
+        }
+        
+        .container {
+            max-width: 1200px;
+            margin: 0 auto;
+            padding: 2rem;
+        }
+        
+        .card {
+            background-color: white;
+            border-radius: 8px;
+            box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
+            padding: 1.5rem;
+            margin-bottom: 2rem;
+        }
+        
+        .card-header {
+            background-color: var(--primary-color);
+            color: white;
+            padding: 1rem;
+            border-radius: 8px 8px 0 0;
+            margin: -1.5rem -1.5rem 1.5rem -1.5rem;
+        }
+        
+        h1, h2, h3, h4 {
+            color: var(--primary-color);
+        }
+        
+        .btn {
+            display: inline-block;
+            background-color: var(--primary-color);
+            color: white;
+            padding: 0.5rem 1rem;
+            border: none;
+            border-radius: 4px;
+            cursor: pointer;
+            font-size: 1rem;
+            transition: background-color 0.3s;
+        }
+        
+        .btn:hover {
+            background-color: #3a5a8a;
+        }
+        
+        .btn-success {
+            background-color: var(--accent-color);
+        }
+        
+        .btn-success:hover {
+            background-color: #218838;
+        }
+        
+        .form-group {
+            margin-bottom: 1rem;
+        }
+        
+        label {
+            display: block;
+            margin-bottom: 0.5rem;
+            font-weight: 500;
+        }
+        
+        input, textarea {
+            width: 100%;
+            padding: 0.5rem;
+            border: 1px solid #ddd;
+            border-radius: 4px;
+            font-size: 1rem;
+        }
+        
+        .response-area {
+            background-color: var(--light-bg);
+            border: 1px solid #ddd;
+            border-radius: 4px;
+            padding: 1rem;
+            margin-top: 1rem;
+            min-height: 100px;
+            white-space: pre-wrap;
+        }
+        
+        .endpoints-list {
+            list-style-type: none;
+            padding: 0;
+        }
+        
+        .endpoints-list li {
+            padding: 0.5rem 0;
+            border-bottom: 1px solid #eee;
+        }
+        
+        .context-id {
+            font-family: monospace;
+            background-color: #f1f1f1;
+            padding: 0.2rem 0.4rem;
+            border-radius: 4px;
+        }
+        
+        .loading {
+            display: none;
+            text-align: center;
+            margin: 1rem 0;
+        }
+        
+        .loading::after {
+            content: "...";
+            animation: dots 1.5s steps(5, end) infinite;
+        }
+        
+        @keyframes dots {
+            0%, 20% { content: "."; }
+            40% { content: ".."; }
+            60%, 100% { content: "..."; }
+        }
+        
+        .error-message {
+            color: #dc3545;
+            margin-top: 0.5rem;
+            display: none;
+        }
+        
+        .success-message {
+            color: var(--accent-color);
+            margin-top: 0.5rem;
+            display: none;
+        }
+        
+        code {
+            font-family: 'Courier New', Courier, monospace;
+            background-color: #f5f5f5;
+            padding: 0.2rem 0.4rem;
+            border-radius: 3px;
+            font-size: 0.9em;
+        }
+        
+        @media (max-width: 768px) {
+            .container {
+                padding: 1rem;
+            }
+            
+            .navbar {
+                flex-direction: column;
+                align-items: flex-start;
+            }
+            
+            .navbar-nav {
+                margin-top: 1rem;
+                flex-direction: column;
+            }
+            
+            .nav-item {
+                margin-left: 0;
+                margin-top: 0.5rem;
+            }
+        }
+    </style>
+</head>
+<body>
+    <nav class="navbar">
+        <a href="#" class="navbar-brand">MCP EdTech</a>
+        <ul class="navbar-nav">
+            <li class="nav-item"><a href="#" class="nav-link">Home</a></li>
+            <li class="nav-item"><a href="#api-demo" class="nav-link">API Demo</a></li>
+            <li class="nav-item"><a href="/docs" class="nav-link">Documentation</a></li>
+            <li class="nav-item"><a href="#" class="nav-link">Developed by M.Habib Agrebi</a></li>
+        </ul>
+    </nav>
+    
+    <div class="container">
+        <div class="card">
+            <h1>Model Context Protocol (MCP) for EdTech</h1>
+            
+            <h2>Welcome to the MCP EdTech Demo</h2>
+            <p>This demo showcases the Model Context Protocol (MCP) implementation for educational technology applications. MCP provides a standardized way for EdTech applications to interact with various AI models while maintaining context and state across interactions.</p>
+            
+            <h3>Key features of this implementation:</h3>
+            <ul>
+                <li>Context management for stateful conversations</li>
+                <li>Student profile management</li>
+                <li>Learning progress tracking</li>
+                <li>Content adaptation based on student profiles</li>
+                <li>Assessment and feedback systems</li>
+            </ul>
+        </div>
+        
+        <div id="api-demo" class="card">
+            <div class="card-header">
+                <h2>API Demo</h2>
+            </div>
+            
+            <h3>Try the MCP API</h3>
+            <p>1. Create a Context</p>
+            <p>First, let's create a new context for our interaction:</p>
+            <button id="createContextBtn" class="btn">Create Context</button>
+            <div id="contextLoading" class="loading">Creating context</div>
+            <div id="contextError" class="error-message"></div>
+            <div id="contextSuccess" class="success-message"></div>
+            <div id="contextResponse" class="response-area" style="display: none;"></div>
+            
+            <p>2. Process an Interaction</p>
+            <p>Now, let's process an interaction using the context we created:</p>
+            <div class="form-group">
+                <label for="interactionInput">Enter your question or prompt:</label>
+                <input type="text" id="interactionInput" placeholder="e.g., Explain the concept of photosynthesis">
+            </div>
+            <button id="processInteractionBtn" class="btn">Process Interaction</button>
+            <div id="interactionLoading" class="loading">Processing interaction</div>
+            <div id="interactionError" class="error-message"></div>
+            <div id="interactionResponse" class="response-area" style="display: none;"></div>
+        </div>
+        
+        <div class="card">
+            <h3>Available Endpoints</h3>
+            <ul class="endpoints-list">
+                <li><strong>Interaction</strong>
+                    <ul>
+                        <li>POST /interact - Process an interaction</li>
+                    </ul>
+                </li>
+                <li><strong>Student Profiles</strong>
+                    <ul>
+                        <li>POST /students - Create student profile</li>
+                        <li>GET /students/{student_id} - Get student information</li>
+                        <li>PUT /students/{student_id} - Update student information</li>
+                    </ul>
+                </li>
+                <li><strong>Content Adaptation</strong>
+                    <ul>
+                        <li>POST /content/adapt - Adapt content for a student</li>
+                    </ul>
+                </li>
+                <li><strong>Models</strong>
+                    <ul>
+                        <li>GET /models - List available models</li>
+                        <li>GET /models/{model_name}/capabilities - Get model capabilities</li>
+                    </ul>
+                </li>
+            </ul>
+            <p>For complete API documentation, visit the <a href="/docs">Swagger UI</a> or <a href="/redoc">ReDoc</a> pages.</p>
+        </div>
+    </div>
+    
+    <footer style="background-color: var(--primary-color); color: white; text-align: center; padding: 1rem; margin-top: 2rem;">
+        <p>Developed by M.Habib Agrebi</p>
+    </footer>
+    
+    <script>
+        let currentContextId = null;
+        
+        document.getElementById('createContextBtn').addEventListener('click', createContext);
+        document.getElementById('processInteractionBtn').addEventListener('click', processInteraction);
+        
+        async function createContext() {
+            const contextLoading = document.getElementById('contextLoading');
+            const contextError = document.getElementById('contextError');
+            const contextSuccess = document.getElementById('contextSuccess');
+            const contextResponse = document.getElementById('contextResponse');
+            
+            contextLoading.style.display = 'block';
+            contextError.style.display = 'none';
+            contextSuccess.style.display = 'none';
+            contextResponse.style.display = 'none';
+            
+            try {
+                const response = await fetch('/context/create', {
+                    method: 'POST',
+                    headers: {
+                        'Content-Type': 'application/json'
+                    },
+                    body: JSON.stringify({
+                        metadata: {
+                            source: 'demo-ui',
+                            created_by: 'demo-user'
+                        }
+                    })
+                });
+                
+                const data = await response.json();
+                
+                if (!response.ok) {
+                    throw new Error(data.detail || 'Failed to create context');
+                }
+                
+                currentContextId = data.context_id;
+                
+                contextResponse.textContent = JSON.stringify(data, null, 2);
+                contextResponse.style.display = 'block';
+                contextSuccess.textContent = `Context created successfully! Context ID: ${currentContextId}`;
+                contextSuccess.style.display = 'block';
+            } catch (error) {
+                contextError.textContent = `Error: ${error.message}`;
+                contextError.style.display = 'block';
+            } finally {
+                contextLoading.style.display = 'none';
+            }
+        }
+        
+        async function processInteraction() {
+            if (!currentContextId) {
+                alert('Please create a context first!');
+                return;
+            }
+            
+            const interactionInput = document.getElementById('interactionInput');
+            const interactionLoading = document.getElementById('interactionLoading');
+            const interactionError = document.getElementById('interactionError');
+            const interactionResponse = document.getElementById('interactionResponse');
+            
+            if (!interactionInput.value.trim()) {
+                alert('Please enter a question or prompt!');
+                return;
+            }
+            
+            interactionLoading.style.display = 'block';
+            interactionError.style.display = 'none';
+            interactionResponse.style.display = 'none';
+            
+            try {
+                const response = await fetch('/interact', {
+                    method: 'POST',
+                    headers: {
+                        'Content-Type': 'application/json'
+                    },
+                    body: JSON.stringify({
+                        context_id: currentContextId,
+                        interaction_type: 'text',
+                        content: {
+                            text: interactionInput.value.trim()
+                        },
+                        format: 'text',
+                        model_name: 'mock'
+                    })
+                });
+                
+                const data = await response.json();
+                
+                if (!response.ok) {
+                    throw new Error(data.detail || 'Failed to process interaction');
+                }
+                
+                interactionResponse.textContent = data.content.text || JSON.stringify(data, null, 2);
+                interactionResponse.style.display = 'block';
+            } catch (error) {
+                interactionError.textContent = `Error: ${error.message}`;
+                interactionError.style.display = 'block';
+            } finally {
+                interactionLoading.style.display = 'none';
+            }
+        }
+    </script>
+</body>
+</html>

storage/students/293fc89c-8969-43ed-9a8f-f3e2131d97cd.json

@@ -0,0 +1,20 @@
+{
+  "id": "293fc89c-8969-43ed-9a8f-f3e2131d97cd",
+  "name": "habib",
+  "educational_level": "graduate",
+  "learning_style": "visual",
+  "interests": [
+    "science",
+    "technology",
+    "art"
+  ],
+  "strengths": [
+    "problem-solving",
+    "creativity"
+  ],
+  "areas_for_improvement": [
+    "time-management"
+  ],
+  "completed_objectives": [],
+  "current_objectives": []
+}