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

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

🚀 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:

python -m src.main

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

🛠️ MCP Tools Reference

The Education MCP Server provides 21+ MCP tools across four API integrations:

📚 Open Library Tools (4 tools)

`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
)

🌐 Wikipedia Tools (5 tools)

`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
)

📖 Dictionary Tools (5 tools)

`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_related_vocabulary`

Get synonyms, antonyms, and related educational terms.

get_related_vocabulary(
    word="democracy",
    relationship_type="related",
    grade_level="9-12",
    limit=10
)

🔬 arXiv Tools (5 tools)

`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
)

🖥️ Server Tools (1 tool)

`get_server_status`

Get comprehensive server status and performance metrics.

get_server_status()

🔌 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):

{
    "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
}
```
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:

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
```
(Note: curl will keep the connection open and print events as they arrive.)

💻 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:

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

📊 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

🧪 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

make validate

🧪 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

Educational Features Guide: Complete educational capabilities
API Reference: Detailed MCP tool documentation
Performance Benchmarks: Real-world test results and metrics
Deployment Guide: Production deployment instructions
Performance Guide: Optimization and monitoring

🔧 Development Status

✅ COMPLETE - All Features Implemented

Core Infrastructure ✅

Project structure and configuration
Core services (caching, rate limiting, usage tracking)
Base models and validation
FastMCP server setup
Educational filtering framework

API Integrations ✅

Open Library API integration (4 tools)
Wikipedia API integration (5 tools)
Dictionary API integration (5 tools)
arXiv API integration (5 tools)
Educational content filtering
Cross-API educational workflows

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.

Name		Name	Last commit message	Last commit date
Latest commit History 21 Commits
config		config
docs		docs
src		src
tests		tests
.env.example		.env.example
.gitignore		.gitignore
LICENSE		LICENSE
Makefile		Makefile
README.md		README.md
pyproject.toml		pyproject.toml
requirements-dev.txt		requirements-dev.txt
requirements.txt		requirements.txt
run_validation_tests.py		run_validation_tests.py

License

Cicatriiz/openedu-mcp

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