Model Context Protocol (MCP) for EdTech
Welcome to the MCP EdTech Demo

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.

Key features of this implementation:

  • Context management for stateful conversations
  • Student profile management
  • Learning progress tracking
  • Content adaptation based on student profiles
  • Assessment and feedback systems
API Demo
Try the MCP API
1. Create a Context

First, let's create a new context for our interaction:

2. Process an Interaction

Now, let's process an interaction using the context we created:

3. Create a Student Profile

Let's create a student profile:

4. Adapt Content for Student

Now, let's adapt some content for the student:

API Documentation
Available Endpoints
Context Management
  • 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
Interaction
  • POST /api/v1/interact - Process an interaction
Student Profiles
  • 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
Progress Tracking
  • GET /api/v1/students/{student_id}/progress - Get learning progress
  • POST /api/v1/assessments - Create assessment
  • GET /api/v1/students/{student_id}/assessments - List student assessments
Content Adaptation
  • POST /api/v1/content/adapt - Adapt content for a student
Learning Paths
  • GET /api/v1/learning-paths/{student_id} - Get personalized learning path
Models
  • GET /api/v1/models - List available models
  • GET /api/v1/models/{model_name}/capabilities - Get model capabilities

For complete API documentation, visit the Swagger UI or ReDoc pages.