MCP Recommender
Provides intelligent recommendations for MCP servers based on development needs using natural language queries. Searches through 874+ curated MCP servers across 36+ categories with advanced matching algorithms.
README
MCP Recommender
A smart MCP (Model Context Protocol) server that provides intelligent recommendations for other MCP servers based on your development needs.
Features
- 🔍 Smart Search: Find MCP servers using natural language queries
- 📊 Rich Database: Access to 874+ curated MCP servers across 36+ categories
- 🎯 Intelligent Matching: Advanced scoring algorithm for relevant recommendations
- 🏷️ Category Filtering: Filter by specific categories and programming languages
- 🚀 Easy Integration: Simple setup with uv package manager
- 🔧 Multiple Interfaces: Support for both CLI and MCP client integration
Installation
Using uv (Recommended)
# Clone the repository
git clone https://github.com/mcp-team/mcp-recommender.git
cd mcp-recommender
# Install with uv
uv sync
# Test the installation
uv run -m mcp_recommender --test
Using pip
pip install mcp-recommender
Usage
Command Line Interface
# Test mode - verify installation and see sample recommendations
uv run -m mcp_recommender --test
# Server mode - start the MCP server
uv run -m mcp_recommender --server
# Debug mode - detailed diagnostic information
uv run -m mcp_recommender --debug
MCP Client Integration
Add to your MCP client configuration:
{
"mcpServers": {
"mcp-recommender": {
"isActive": true,
"name": "mcp-recommender",
"type": "stdio",
"command": "uv",
"args": [
"--directory",
"/path/to/mcp-recommender",
"run",
"-m",
"mcp_recommender"
]
}
}
}
Available Tools
Once integrated, you can use these tools in your MCP client:
recommend_mcp
Get intelligent MCP server recommendations based on your needs.
Parameters:
query(string): Description of functionality you needlimit(integer, optional): Maximum number of recommendations (default: 5)category(string, optional): Filter by specific categorylanguage(string, optional): Filter by programming language
Example:
recommend_mcp("database operations with SQLite", limit=3)
list_categories
List all available MCP categories with counts.
get_functional_keywords
Show functional keyword mappings for better search results.
Categories
The recommender covers 36+ categories including:
- Developer Tools (120+ servers)
- Databases (79+ servers)
- Search & Data Extraction (69+ servers)
- Cloud Platforms (39+ servers)
- Security (39+ servers)
- Communication (36+ servers)
- Browser Automation (23+ servers)
- Knowledge & Memory (22+ servers)
- And many more...
Development
Setup Development Environment
# Clone and setup
git clone https://github.com/mcp-team/mcp-recommender.git
cd mcp-recommender
# Install development dependencies
uv sync --dev
# Run tests
uv run pytest
# Build package
uv build
Project Structure
mcp-recommender/
├── mcp_recommender/ # Main package
│ ├── __init__.py
│ ├── __main__.py # CLI entry point
│ ├── server.py # MCP server implementation
│ └── data/ # MCP database and keywords
│ ├── mcp_database.json
│ └── functional_keywords.json
├── tests/ # Test suite
├── LICENSE # MIT License
├── README.md # This file
└── pyproject.toml # Package configuration
Contributing
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
License
This project is licensed under the MIT License - see the LICENSE file for details.
Acknowledgments
- Built with FastMCP framework
- MCP database curated from the awesome MCP community
- Powered by the Model Context Protocol
Support
Made with ❤️ by the MCP community
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