# 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