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.
🎓 Features
Complete API Integration Suite
- 📚 Open Library Integration: Educational book search, recommendations, and metadata
- 🌐 Wikipedia Integration: Educational article analysis with grade-level filtering
- 📖 Dictionary Integration: Vocabulary analysis and language learning support
- 🔬 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
- 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
🚀 Quick Start
Prerequisites
- Python 3.9 or higher
- pip package manager
Installation
- Clone the repository:
git clone https://github.com/Cicatriiz/openedu-mcp.git
cd openedu-mcp
- Install dependencies:
pip install -r requirements.txt
- Set up configuration:
cp .env.example .env
# Edit .env with your preferred settings if needed
- Run the server:
- Test the installation:
python run_validation_tests.py
Development Setup
For development, install additional dependencies:
pip install -r requirements-dev.txt
Run tests:
# Unit tests
pytest tests/
# Integration tests
pytest tests/test_integration/
# Performance tests
pytest tests/test_performance.py
Format code:
black src tests
isort src tests
The Education MCP Server provides 21+ MCP tools across four API integrations:
search_educational_books
Search for educational books with grade-level and subject filtering.
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.
get_book_details_by_isbn(
isbn="9780134685991",
include_cover=True
)
search_books_by_subject
Search books by educational subject with curriculum alignment.
search_books_by_subject(
subject="Science",
grade_level="3-5",
limit=10
)
get_book_recommendations
Get curated book recommendations for specific grade levels.
get_book_recommendations(
grade_level="9-12",
subject="Physics",
limit=5
)
search_educational_articles
Search Wikipedia articles with educational filtering and analysis.
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.
get_article_summary(
title="Solar System",
include_educational_analysis=True
)
get_article_content
Get full article content with educational enrichment.
get_article_content(
title="Photosynthesis",
include_images=True
)
get_featured_article
Get Wikipedia's featured article with educational analysis.
get_featured_article(
date="2024/01/15",
language="en"
)
get_articles_by_subject
Get articles by educational subject with grade-level filtering.
get_articles_by_subject(
subject="Mathematics",
grade_level="6-8",
limit=10
)
get_word_definition
Get educational word definitions with grade-appropriate complexity.
get_word_definition(
word="ecosystem",
grade_level="6-8",
include_pronunciation=True
)
get_vocabulary_analysis
Analyze word complexity and educational value.
get_vocabulary_analysis(
word="photosynthesis",
context="plant biology lesson"
)
get_word_examples
Get educational examples and usage contexts for vocabulary.
get_word_examples(
word="fraction",
grade_level="3-5",
subject="Mathematics"
)
get_pronunciation_guide
Get phonetic information and pronunciation guides.
get_pronunciation_guide(
word="photosynthesis",
include_audio=True
)
Get synonyms, antonyms, and related educational terms.
get_related_vocabulary(
word="democracy",
relationship_type="related",
grade_level="9-12",
limit=10
)
search_academic_papers
Search academic papers with educational relevance filtering.
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.
get_paper_summary(
paper_id="2301.00001",
include_educational_analysis=True
)
get_recent_research
Get recent research papers by educational subject.
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.
get_research_by_level(
academic_level="Graduate",
subject="Mathematics",
max_results=10
)
analyze_research_trends
Analyze research trends for educational insights.
analyze_research_trends(
subject="Artificial Intelligence",
days=90
)
get_server_status
Get comprehensive server status and performance metrics.
🔌 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.
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"
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):
{
"jsonrpc": "2.0",
"method": "<tool_name>",
"params": {"param1": "value1", ...},
"id": "your_request_id"
}
- Example
curl call to handle_stdio_input: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:
{
"jsonrpc": "2.0",
"result": "Processed: HELLO FROM HTTP",
"id": 1
}
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>
- 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: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:curl -N -H "Accept:text/event-stream" http://localhost:8000/events
curl will keep the connection open and print events as they arrive.)
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:
- Go to
Cursor Settings > MCP. - Click
+ Add new Global MCP Server. - Alternatively, add the following configuration to your global
.cursor/mcp.json file (ensure cwd points to the root directory of this project):
{
"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):
- Navigate to
Windsurf - Settings > Advanced Settings or use the Command Palette to Open Windsurf Settings Page. - 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):
{
"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):
{
"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):
{
"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):
{
"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.
📋 Educational Use Cases
Elementary Education (K-2)
# 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)
# 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)
# 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
# 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"
)
⚙️ Configuration
Configuration Files
The server uses YAML configuration files in the config/ directory:
# 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:
export OPENEDU_MCP_CACHE_TTL=7200
export OPENEDU_MCP_LOG_LEVEL=DEBUG
export OPENEDU_MCP_RATE_LIMIT_WIKIPEDIA=300
🏗️ Architecture
Education MCP Server
├── API Layer (FastMCP)
│ ├── 20+ MCP Tools
│ └── Request/Response Handling
├── Service Layer
│ ├── Cache Service (SQLite)
│ ├── Rate Limiting Service
│ └── Usage Tracking Service
├── Tool Layer
│ ├── Open Library Tools
│ ├── Wikipedia Tools
│ ├── Dictionary Tools
│ └── arXiv Tools
├── API Layer
│ ├── Open Library API
│ ├── Wikipedia API
│ ├── Dictionary API
│ └── arXiv API
└── Data Layer
├── Educational Models
├── Cache Database
└── Usage Analytics
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
🧪 Testing
Run All Tests
# 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
pytest --cov=src --cov-report=html
open htmlcov/index.html
Validation Tests
🧪 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
python run_validation_tests.py
The script will:
- Test all API integrations (Open Library, Wikipedia, Dictionary, arXiv)
- Validate educational workflows:
- Elementary Education (K-2)
- High School STEM (9-12)
- College Research
- Educator Resources
- Measure performance metrics:
- Response times for each API
- Cache hit/miss rates
- Rate limiting effectiveness
- Educational filtering processing time
- Generate a detailed JSON report with test results and performance statistics
Test Cases
- 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
- 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
- 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
- arXiv:
- Search for "machine learning" papers with educational filtering
- Get recent AI research papers
- Verify academic level assessment
- Test research trend analysis
📚 Documentation
🔧 Development Status
✅ COMPLETE - All Features Implemented
Core Infrastructure ✅
API Integrations ✅
Testing & Documentation ✅
🤝 Contributing
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Make your changes
- Add tests for new functionality
- Run the test suite (
pytest) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - 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
📄 License
This project is licensed under the MIT License.
🆘 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
🙏 Acknowledgments
- Built with 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.