Mcp Mcp

What is Mcp Mcp about?

Mcp Mcp serves as a "phone book" for MCP servers. It aggregates thousands of server definitions from official listings and community‑curated collections, deduplicates them, and stores them in a database that can be queried semantically.

How to use Mcp Mcp?

1. Install – the package can be installed via uvx (or pipx) after cloning the repository.
2. Configure – add an entry to the Claude Desktop or Claude Code configuration pointing to the mcp-mcp command.
3. Run – start the server in STDIO mode (uv run main.py) or HTTP mode (uv run main.py --http).
4. Query – ask your AI assistant (e.g., Claude) to find a server by describing the needed capability, and Mcp Mcp will return matching server definitions.

Key features of Mcp Mcp

• 1,728+ MCP servers aggregated from official and community sources.
• Automatic updates every 3 hours to keep the registry fresh.
• Semantic search using pre‑computed embeddings for sub‑second response times.
• Multi‑transport support: STDIO (for native MCP clients) and HTTP.
• Easy development workflow with just commands, auto‑reload, and full test suite.
• Security middleware to validate request origins.

Use cases of Mcp Mcp

• An AI assistant needs real‑time weather data – it asks Mcp Mcp and receives a ready‑to‑use MCP server endpoint.
• Developers building autonomous agents can dynamically discover new capabilities without hard‑coding server URLs.
• Organizations can maintain a private registry by extending the database with additional entries.
• Rapid prototyping of tool‑augmented AI workflows by pulling in community‑maintained servers.

FAQ from the Mcp Mcp

Q: Do I need to run my own instance? A: Yes, Mcp Mcp is a self‑hosted service; you can run it locally or deploy it in a container for production.

Q: Which Python version is required? A: Python 3.13 or newer.

Q: How are duplicate servers avoided? A: An intelligent deduplication process merges entries across sources.

Q: Can I contribute new server definitions? A: Absolutely – fork the repo, add entries to the source lists, and submit a pull request.

Q: Is there a Docker image? A: Not yet, but Docker support is on the roadmap.

MCP-MCP: Meta-MCP Server

MCP-MCP is a Meta-MCP Server that acts as a tool discovery and provisioning service for the Model Context Protocol (MCP). When an AI assistant needs a capability that isn't currently available, it can ask MCP-MCP to discover and suggest appropriate MCP servers from a comprehensive database of over a thousand servers aggregated from multiple curated sources.

Think of it as a "phone book" for MCP servers - one tool to find all other tools.

🗃️ 1,728+ MCP Servers Available

MCP-MCP provides access to a comprehensive database aggregated from multiple curated sources, including:

• Official MCP Servers (modelcontextprotocol/servers)
• Community Collections (Punkpeye & Appcypher awesome lists)
• Intelligent Deduplication ensures no duplicates across sources

The database is automatically updated every 3 hours with the latest servers from the community.

Motivation

Agents Just Wanna Have Tools

• Agents know what they need: AI assistants can clearly articulate requirements like "check domain availability" or "get weather data"
• Web search isn't always enough: Generic search results don't always provide realtime data
• CLI tools require setup: Many tools need complex installation, configuration, and API keys - agents have to repeat this setup every single time they need to complete a task
• MCP servers are scattered: Great tools exist but discovering them requires manual research across GitHub, forums, and documentation

Why make agents (and users) hunt for tools when we can bring the tools to them?

Quick Start

Claude Desktop Configuration

Add MCP-MCP to your Claude Desktop configuration file:

Configuration File Location:

• macOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

Configuration:

{
  "mcpServers": {
    "mcp-mcp": {
      "command": "uvx",
      "args": ["mcp-mcp"]
    }
  }
}

Alternative with pipx:

{
  "mcpServers": {
    "mcp-mcp": {
      "command": "mcp-mcp"
    }
  }
}

Claude Code Configuration

Add MCP-MCP to your Claude Code configuration file:

claude mcp add mcp-mcp uvx mcp-mcp

Usage Examples

Once configured, you can ask Claude Desktop to discover MCP servers using natural language:

• "Find me an MCP server for weather data"
• "I need a server for checking domain availability"
• "Search for MCP servers related to stock market data"
• "What MCP servers are available for web scraping?"

Development

Prerequisites

• Python 3.13+
• uv package manager
• direnv (optional, for automatic environment setup)
• just (optional, for convenient development commands)

Setup

# Clone the repository
git clone https://github.com/your-username/mcp-mcp.git
cd mcp-mcp

# Install dependencies
uv sync

# Run tests
uv run pytest

# Run the server
uv run main.py

Install via uvx (for testing)

For testing the installed package:

uvx mcp-mcp

This installs and runs the MCP-MCP server directly via uvx.

Development Commands (with justfile)

This project includes a justfile for common development tasks:

# List all available commands
just help

# Development with auto-reload
just dev      # STDIO mode with file watching
just dev-http # HTTP mode with file watching

# Running without auto-reload
just run-stdio # STDIO mode
just run-http  # HTTP mode

# Testing
just test             # Unit tests only
just test-integration # Include GitHub integration tests

# Building and publishing
just build           # Build package
just publish-test    # Publish to Test PyPI
just publish-prod    # Publish to Production PyPI

# Utilities
just version # Show version
just clean   # Clean build artifacts

Development Mode

For development and testing, use HTTP transport (easier to stop with Ctrl+C):

# HTTP mode (accessible at http://localhost:8000)
uv run main.py --http
# OR with justfile:
just run-http

# With auto-reload during development
just dev-http

# Custom host/port
uv run main.py --http --host 0.0.0.0 --port 3000

# STDIO mode (for MCP clients like Claude Desktop)
uv run main.py  # Note: To stop STDIO mode, use Ctrl+D (EOF), not Ctrl+C
# OR with justfile:
just run-stdio

# With auto-reload during development
just dev

Building

# Build package
uv build
# OR with justfile:
just build

# Test local installation
uvx --from ./dist/mcp_mcp-0.1.0-py3-none-any.whl mcp-mcp

Command Line Options

mcp-mcp --help

Option	Description	Default
--transport {stdio,http}	Transport method	stdio
--http	Use HTTP transport	-
--host HOST	Host for HTTP transport	localhost
--port PORT	Port for HTTP transport	8000

Testing

# Run all tests (unit + integration)
uv run pytest
# OR with justfile:
just test

# Run only unit tests (fast, no network)
uv run pytest db/ -v
# OR with justfile:
just test-unit

# Run only integration/e2e tests
uv run pytest tests/ -v
# OR with justfile:
just test-integration

# Run GitHub integration tests (optional, requires network)
MCP_MCP_TEST_GITHUB_INTEGRATION=1 uv run pytest tests/
# OR with justfile:
just test-integration-github

# Run all tests including GitHub integration
MCP_MCP_TEST_GITHUB_INTEGRATION=1 uv run pytest
# OR with justfile:
just test-all

# Run with coverage
uv run pytest --cov=db

Test Structure:

• Unit Tests: Located in db/ alongside the code they test (Go-style)
• Integration/E2E Tests: Located in tests/ directory

Integration Tests: Set MCP_MCP_TEST_GITHUB_INTEGRATION=1 to test real GitHub downloads and verify the complete first-user onboarding experience. These tests ensure users get fast startup (< 5 seconds) with 1,728+ servers.

Roadmap

Current Status: MVP Complete ✅

• ✅ Multi-source discovery (3 curated sources, 1,728+ unique servers)
• ✅ Semantic search with precomputed embeddings for sub-second response
• ✅ Production distribution via uvx/pipx with automated releases
• ✅ Security hardened with origin validation middleware
• ✅ Comprehensive test coverage (65+ tests)
• ✅ Complete documentation and development workflow

Future Enhancements (Beyond MVP)

• Docker integration for automatic server containerization
• MCP protocol proxy for seamless server execution
• GitHub API integration for live server discovery
• Server lifecycle management and cleanup
• Private registry support
• Dependency resolution
• Performance monitoring
• Web UI for server management

Contributing

We welcome contributions! Please see our development setup and:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Development Guidelines

• Follow Python 3.13+ best practices
• Add tests for new functionality
• Update documentation as needed
• Use semantic commit messages

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Model Context Protocol team at Anthropic
• Open source MCP server maintainers and contributors
• MCP Server Lists:
  • Official MCP Servers
  • Punkpeye's Awesome MCP Servers
  • Appcypher's Awesome MCP Servers

---

Made with ❤️ for the MCP ecosystem