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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 | |