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OpenEdu MCP Server

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# OpenEdu MCP Server A comprehensive Model Context Protocol (MCP) server designed to provide educational resources and support curriculum planning for educators. This server integrates with multiple educational APIs to provide access to books, articles, definitions, and research papers with intelligent educational filtering and grade-level appropriateness. ## πŸŽ“ Features ### Complete API Integration Suite - **πŸ“š Open Library Integration**: Educational book search, recommendations, and metadata - **🌐 Wikipedia Integration**: Educational article analysis with grade-level filtering - **πŸ“– Dictionary Integration**: Vocabulary analysis and language learning support - **πŸ”¬ arXiv Integration**: Academic paper search with educational relevance scoring ### Educational Intelligence - **Grade Level Filtering**: K-2, 3-5, 6-8, 9-12, College level content - **Subject Classification**: Mathematics, Science, ELA, Social Studies, Arts, PE, Technology - **Curriculum Alignment**: Common Core, NGSS, State Standards support - **Educational Metadata**: Complexity scoring, reading levels, educational value assessment ### Performance & Reliability - **Intelligent Caching**: SQLite-based caching with TTL support - **Rate Limiting**: Built-in rate limiting to respect API quotas - **Usage Analytics**: Comprehensive usage tracking and performance metrics - **Error Handling**: Robust error handling with educational context preservation ## πŸš€ Quick Start ### Prerequisites - Python 3.9 or higher - pip package manager ### Installation 1. **Clone the repository:** ```bash git clone https://github.com/Cicatriiz/openedu-mcp.git cd openedu-mcp ``` 2. **Install dependencies:** ```bash pip install -r requirements.txt ``` 3. **Set up configuration:** ```bash cp .env.example .env # Edit .env with your preferred settings if needed ``` 4. **Run the server:** ```bash python -m src.main ``` 5. **Test the installation:** ```bash python run_validation_tests.py ``` ### Development Setup For development, install additional dependencies: ```bash pip install -r requirements-dev.txt ``` Run tests: ```bash # Unit tests pytest tests/ # Integration tests pytest tests/test_integration/ # Performance tests pytest tests/test_performance.py ``` Format code: ```bash black src tests isort src tests ``` ## πŸ› οΈ MCP Tools Reference The Education MCP Server provides **21+ MCP tools** across four API integrations: ### πŸ“š Open Library Tools (4 tools) #### `search_educational_books` Search for educational books with grade-level and subject filtering. ```python search_educational_books( query="mathematics", subject="Mathematics", grade_level="6-8", limit=10 ) ``` #### `get_book_details_by_isbn` Get detailed book information by ISBN with educational metadata. ```python get_book_details_by_isbn( isbn="9780134685991", include_cover=True ) ``` #### `search_books_by_subject` Search books by educational subject with curriculum alignment. ```python search_books_by_subject( subject="Science", grade_level="3-5", limit=10 ) ``` #### `get_book_recommendations` Get curated book recommendations for specific grade levels. ```python get_book_recommendations( grade_level="9-12", subject="Physics", limit=5 ) ``` ### 🌐 Wikipedia Tools (5 tools) #### `search_educational_articles` Search Wikipedia articles with educational filtering and analysis. ```python search_educational_articles( query="photosynthesis", grade_level="3-5", subject="Science", limit=5 ) ``` #### `get_article_summary` Get article summaries with educational metadata and complexity analysis. ```python get_article_summary( title="Solar System", include_educational_analysis=True ) ``` #### `get_article_content` Get full article content with educational enrichment. ```python get_article_content( title="Photosynthesis", include_images=True ) ``` #### `get_featured_article` Get Wikipedia's featured article with educational analysis. ```python get_featured_article( date="2024/01/15", language="en" ) ``` #### `get_articles_by_subject` Get articles by educational subject with grade-level filtering. ```python get_articles_by_subject( subject="Mathematics", grade_level="6-8", limit=10 ) ``` ### πŸ“– Dictionary Tools (5 tools) #### `get_word_definition` Get educational word definitions with grade-appropriate complexity. ```python get_word_definition( word="ecosystem", grade_level="6-8", include_pronunciation=True ) ``` #### `get_vocabulary_analysis` Analyze word complexity and educational value. ```python get_vocabulary_analysis( word="photosynthesis", context="plant biology lesson" ) ``` #### `get_word_examples` Get educational examples and usage contexts for vocabulary. ```python get_word_examples( word="fraction", grade_level="3-5", subject="Mathematics" ) ``` #### `get_pronunciation_guide` Get phonetic information and pronunciation guides. ```python get_pronunciation_guide( word="photosynthesis", include_audio=True ) ``` #### `get_related_vocabulary` Get synonyms, antonyms, and related educational terms. ```python get_related_vocabulary( word="democracy", relationship_type="related", grade_level="9-12", limit=10 ) ``` ### πŸ”¬ arXiv Tools (5 tools) #### `search_academic_papers` Search academic papers with educational relevance filtering. ```python search_academic_papers( query="machine learning education", academic_level="Undergraduate", subject="Computer Science", max_results=10 ) ``` #### `get_paper_summary` Get paper summaries with educational analysis and accessibility scoring. ```python get_paper_summary( paper_id="2301.00001", include_educational_analysis=True ) ``` #### `get_recent_research` Get recent research papers by educational subject. ```python get_recent_research( subject="Physics", days=30, academic_level="High School", max_results=5 ) ``` #### `get_research_by_level` Get research papers appropriate for specific academic levels. ```python get_research_by_level( academic_level="Graduate", subject="Mathematics", max_results=10 ) ``` #### `analyze_research_trends` Analyze research trends for educational insights. ```python analyze_research_trends( subject="Artificial Intelligence", days=90 ) ``` ### πŸ–₯️ Server Tools (1 tool) #### `get_server_status` Get comprehensive server status and performance metrics. ```python get_server_status() ``` ## πŸ”Œ Connectivity Endpoints This section details how to interact with the OpenEdu MCP Server through various interfaces, including direct standard I/O, HTTP for tool execution, and Server-Sent Events for real-time updates. ### Stdio Tool (`handle_stdio_input`) The server includes a tool designed for direct command-line or piped input. - **Tool Name**: `handle_stdio_input` - **Description**: Processes a single line of text input and returns a transformed version. This is useful for basic interaction or scripting with the MCP server if it's configured to listen to stdin. - **Signature**: `async def handle_stdio_input(ctx: Context, input_string: str) -> str` - **Example Interaction**: ``` Tool: handle_stdio_input Input: "your text here" Output: "Processed: YOUR TEXT HERE" ``` ### HTTP Endpoint for MCP Tools All registered MCP tools (including `handle_stdio_input` and the 20+ tools listed above) are accessible via HTTP. This allows integration with various applications and services. The server likely uses a JSON RPC style for these interactions. - **Endpoint**: `POST /mcp` (This is a common convention for FastMCP servers supporting JSON RPC) - **Request Method**: `POST` - **Headers**: `Content-Type: application/json` - **Request Body Structure (JSON RPC)**: ```json { "jsonrpc": "2.0", "method": "<tool_name>", "params": {"param1": "value1", ...}, "id": "your_request_id" } ``` - **Example `curl` call to `handle_stdio_input`**: ```bash curl -X POST -H "Content-Type: application/json" \ -d '{"jsonrpc": "2.0", "method": "handle_stdio_input", "params": {"input_string": "hello from http"}, "id": 1}' \ http://localhost:8000/mcp ``` - **Expected Response**: ```json { "jsonrpc": "2.0", "result": "Processed: HELLO FROM HTTP", "id": 1 } ``` If an error occurs, the `result` field will be replaced by an `error` object containing `code` and `message`. ### Server-Sent Events (SSE) Endpoint The server provides an SSE endpoint for real-time notifications. This is useful for clients that need to stay updated with server-initiated events. - **Endpoint**: `GET /events` - **Description**: Streams events from the server to the client. - **Event Format**: Each event is sent as a block of text: ``` event: <event_type> data: <json_payload_of_the_event_data> id: <optional_event_id> ``` (Note: An empty line separates events.) - **Known Events**: - **`connected`**: Sent once when the client successfully connects to the SSE stream. - `data`: `{"message": "Successfully connected to SSE stream"}` - **`ping`**: Sent periodically as a heartbeat to keep the connection alive and indicate server health. - `data`: `{"heartbeat": <loop_count>, "message": "ping"}` (loop_count increments) - **`error`**: Sent if an error occurs within the SSE generation stream. - `data`: `{"error": "<error_message>"}` - **Example: Connecting with JavaScript's `EventSource`**: ```javascript const evtSource = new EventSource("http://localhost:8000/events"); evtSource.onopen = function() { console.log("Connection to SSE opened."); }; evtSource.onmessage = function(event) { // Generic message handler if no specific event type is matched console.log("Generic message:", event.data); try { const parsedData = JSON.parse(event.data); console.log("Parsed generic data:", parsedData); } catch (e) { // Data might not be JSON } }; evtSource.addEventListener("connected", function(event) { console.log("Event: connected"); console.log("Data:", JSON.parse(event.data)); }); evtSource.addEventListener("ping", function(event) { console.log("Event: ping"); console.log("Data:", JSON.parse(event.data)); }); evtSource.addEventListener("error", function(event) { if (event.target.readyState === EventSource.CLOSED) { console.error("SSE Connection was closed.", event); } else if (event.target.readyState === EventSource.CONNECTING) { console.error("SSE Connection is reconnecting...", event); } else { // An error occurred while streaming, data might be available console.error("SSE Error:", event); if (event.data) { try { console.error("Error Data:", JSON.parse(event.data)); } catch (e) { console.error("Error Data (raw):", event.data); } } } }); ``` - **Example: Connecting with `curl`**: ```bash curl -N -H "Accept:text/event-stream" http://localhost:8000/events ``` *(Note: `curl` will keep the connection open and print events as they arrive.)* ## πŸ’» Editor & AI Tool Integration You can integrate the OpenEdu MCP Server with various AI-assisted coding tools and IDE plugins. This allows these tools to leverage the server's educational functionalities directly within your development environment. Configuration typically involves telling the editor how to start and communicate with the OpenEdu MCP server. The server is run using `python -m src.main` from the root of this project. Below are example configurations for some popular tools. You may need to adjust paths (e.g., for `cwd` or if you have a specific Python environment) based on your local setup. ### Cursor To add this server to Cursor IDE: 1. Go to `Cursor Settings > MCP`. 2. Click `+ Add new Global MCP Server`. 3. Alternatively, add the following configuration to your global `.cursor/mcp.json` file (ensure `cwd` points to the root directory of this project): ```json { "mcpServers": { "openedu-mcp-server": { "command": "python", "args": [ "-m", "src.main" ], "cwd": "/path/to/your/openedu-mcp" // Replace with the actual path to this project's root } } } ``` See the Cursor documentation for more details. ### Windsurf To set up MCP with Windsurf (formerly Cascade): 1. Navigate to `Windsurf - Settings > Advanced Settings` or use the Command Palette to `Open Windsurf Settings Page`. 2. Scroll down to the Cascade section and add the OpenEdu MCP server directly in `mcp_config.json` (ensure `cwd` points to the root directory of this project): ```json { "mcpServers": { "openedu-mcp-server": { "command": "python", "args": [ "-m", "src.main" ], "cwd": "/path/to/your/openedu-mcp" // Replace with the actual path to this project's root } } } ``` ### Cline Add the following JSON manually to your `cline_mcp_settings.json` via Cline's MCP Server setting (ensure `cwd` points to the root directory of this project): ```json { "mcpServers": { "openedu-mcp-server": { "command": "python", "args": [ "-m", "src.main" ], "cwd": "/path/to/your/openedu-mcp" // Replace with the actual path to this project's root } } } ``` ### Roo Code Access the MCP settings by clicking `Edit MCP Settings` in Roo Code settings or using the `Roo Code: Open MCP Config` command in VS Code's command palette (ensure `cwd` points to the root directory of this project): ```json { "mcpServers": { "openedu-mcp-server": { "command": "python", "args": [ "-m", "src.main" ], "cwd": "/path/to/your/openedu-mcp" // Replace with the actual path to this project's root } } } ``` ### Claude Add the following to your `claude_desktop_config.json` file (ensure `cwd` points to the root directory of this project): ```json { "mcpServers": { "openedu-mcp-server": { "command": "python", "args": [ "-m", "src.main" ], "cwd": "/path/to/your/openedu-mcp" // Replace with the actual path to this project's root } } } ``` See the Claude Desktop documentation for more details if available. ## πŸ“‹ Educational Use Cases ### Elementary Education (K-2) ```python # Find age-appropriate books books = await search_educational_books( query="animals", grade_level="K-2", subject="Science" ) # Get simple definitions definition = await get_word_definition( word="habitat", grade_level="K-2" ) # Find educational articles articles = await search_educational_articles( query="animal homes", grade_level="K-2" ) ``` ### Middle School STEM (6-8) ```python # Get math textbooks books = await search_books_by_subject( subject="Mathematics", grade_level="6-8" ) # Analyze vocabulary complexity analysis = await get_vocabulary_analysis( word="equation", context="solving math problems" ) # Find related terms related = await get_related_vocabulary( word="algebra", grade_level="6-8" ) ``` ### High School Advanced (9-12) ```python # Get physics recommendations books = await get_book_recommendations( grade_level="9-12", subject="Physics" ) # Get detailed articles article = await get_article_content( title="Quantum mechanics" ) # Find accessible research papers = await search_academic_papers( query="climate change", academic_level="High School" ) ``` ### College Research ```python # Find academic textbooks books = await search_educational_books( query="calculus", grade_level="College" ) # Get recent research research = await get_recent_research( subject="Computer Science", academic_level="Graduate" ) # Analyze trends trends = await analyze_research_trends( subject="Machine Learning" ) ``` ## βš™οΈ Configuration ### Configuration Files The server uses YAML configuration files in the `config/` directory: ```yaml # config/default.yaml server: name: "openedu-mcp-server" version: "1.0.0" education: grade_levels: - "K-2" - "3-5" - "6-8" - "9-12" - "College" subjects: - "Mathematics" - "Science" - "English Language Arts" - "Social Studies" - "Arts" - "Physical Education" - "Technology" apis: open_library: rate_limit: 100 # requests per minute wikipedia: rate_limit: 200 # requests per minute dictionary: rate_limit: 450 # requests per hour arxiv: rate_limit: 3 # requests per second ``` ### Environment Variables Override configuration with environment variables: ```bash export OPENEDU_MCP_CACHE_TTL=7200 export OPENEDU_MCP_LOG_LEVEL=DEBUG export OPENEDU_MCP_RATE_LIMIT_WIKIPEDIA=300 ``` ## πŸ—οΈ Architecture ``` Education MCP Server β”œβ”€β”€ API Layer (FastMCP) β”‚ β”œβ”€β”€ 20+ MCP Tools β”‚ └── Request/Response Handling β”œβ”€β”€ Service Layer β”‚ β”œβ”€β”€ Cache Service (SQLite) β”‚ β”œβ”€β”€ Rate Limiting Service β”‚ └── Usage Tracking Service β”œβ”€β”€ Tool Layer β”‚ β”œβ”€β”€ Open Library Tools β”‚ β”œβ”€β”€ Wikipedia Tools β”‚ β”œβ”€β”€ Dictionary Tools β”‚ └── arXiv Tools β”œβ”€β”€ API Layer β”‚ β”œβ”€β”€ Open Library API β”‚ β”œβ”€β”€ Wikipedia API β”‚ β”œβ”€β”€ Dictionary API β”‚ └── arXiv API └── Data Layer β”œβ”€β”€ Educational Models β”œβ”€β”€ Cache Database └── Usage Analytics ``` ## πŸ“Š Performance ### Caching Strategy - **Cache Hit Rate**: >70% for repeated queries - **Response Time**: <500ms for cached requests, <2000ms for uncached - **Cache Size**: Configurable with automatic cleanup - **TTL Management**: Intelligent expiration based on content type ### Rate Limiting - **Open Library**: 100 requests/minute - **Wikipedia**: 200 requests/minute - **Dictionary**: 450 requests/hour - **arXiv**: 3 requests/second ### Concurrent Handling - **Async Operations**: Non-blocking I/O for all API calls - **Connection Pooling**: Efficient HTTP connection management - **Resource Limits**: Configurable memory and disk usage limits ## πŸ§ͺ Testing ### Run All Tests ```bash # Unit tests pytest tests/test_tools/ -v # Integration tests pytest tests/test_integration/ -v # Performance tests pytest tests/test_performance.py -v # Real API tests (requires internet) make validate ``` ### Test Coverage ```bash pytest --cov=src --cov-report=html open htmlcov/index.html ``` ### Validation Tests ```bash make validate ``` ## πŸ§ͺ Real API Validation Tests We've implemented comprehensive real-world validation tests to ensure production readiness. These tests verify functionality against live services, not mocks. ### Features - Tests all 20+ MCP tools against their respective live APIs - Validates educational workflows for different grade levels - Measures performance metrics (response times, cache rates, error rates) - Tests error handling with invalid inputs and edge cases - Verifies caching behavior with real API responses ### Running Validation Tests ```bash python run_validation_tests.py ``` The script will: 1. Test all API integrations (Open Library, Wikipedia, Dictionary, arXiv) 2. Validate educational workflows: - Elementary Education (K-2) - High School STEM (9-12) - College Research - Educator Resources 3. Measure performance metrics: - Response times for each API - Cache hit/miss rates - Rate limiting effectiveness - Educational filtering processing time 4. Generate a detailed JSON report with test results and performance statistics ### Test Cases 1. **Open Library**: - Search for "Harry Potter" with grade-level filtering - Get book details by ISBN (e.g., 9780439064866) - Check availability for a known book - Verify educational metadata enrichment 2. **Wikipedia**: - Search for "Quantum Mechanics" with academic level filtering - Get article summary for "Albert Einstein" - Retrieve featured article of the day - Verify content analysis and complexity scoring 3. **Dictionary API**: - Get definition for "photosynthesis" with educational context - Test pronunciation guide for "quinoa" - Verify vocabulary analysis for STEM terms - Test grade-level appropriate definitions 4. **arXiv**: - Search for "machine learning" papers with educational filtering - Get recent AI research papers - Verify academic level assessment - Test research trend analysis ## πŸ“š Documentation - **[Educational Features Guide](docs/EDUCATIONAL_FEATURES.md)**: Complete educational capabilities - **[API Reference](docs/API_REFERENCE.md)**: Detailed MCP tool documentation - **[Performance Benchmarks](docs/PERFORMANCE.md)**: Real-world test results and metrics - **[Deployment Guide](docs/DEPLOYMENT.md)**: Production deployment instructions - **[Performance Guide](docs/PERFORMANCE.md)**: Optimization and monitoring ## πŸ”§ Development Status **βœ… COMPLETE - All Features Implemented** ### Core Infrastructure βœ… - [x] Project structure and configuration - [x] Core services (caching, rate limiting, usage tracking) - [x] Base models and validation - [x] FastMCP server setup - [x] Educational filtering framework ### API Integrations βœ… - [x] Open Library API integration (4 tools) - [x] Wikipedia API integration (5 tools) - [x] Dictionary API integration (5 tools) - [x] arXiv API integration (5 tools) - [x] Educational content filtering - [x] Cross-API educational workflows ### Testing & Documentation βœ… - [x] Comprehensive unit tests - [x] Integration test suite - [x] Performance benchmarks - [x] Demo script with all features - [x] Complete documentation - [x] API reference guide ## 🀝 Contributing 1. Fork the repository 2. Create a feature branch (`git checkout -b feature/amazing-feature`) 3. Make your changes 4. Add tests for new functionality 5. Run the test suite (`pytest`) 6. Commit your changes (`git commit -m 'Add amazing feature'`) 7. Push to the branch (`git push origin feature/amazing-feature`) 8. Open a Pull Request ### Development Guidelines - Follow PEP 8 style guidelines - Add type hints for all functions - Include docstrings for all public methods - Write tests for new features - Update documentation as needed ## πŸ“„ License This project is licensed under the MIT License. ## πŸ†˜ Support For questions, issues, or contributions: - **Issues**: Create an issue in the repository - **Documentation**: Check the `docs/` directory - **Discussions**: Use GitHub Discussions for questions - **Email**: Contact the maintainers ## πŸ™ Acknowledgments - Built with [FastMCP](https://github.com/jlowin/fastmcp) framework - Integrates with Open Library, Wikipedia, Dictionary API, and arXiv - Designed for educational use cases and curriculum planning - Inspired by the need for accessible educational technology --- **OpenEdu MCP Server** - Empowering educators with intelligent educational resource discovery and curriculum planning tools.

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