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servers

MCP.Pizza Chef: modelcontextprotocol

Helps you connect your AI assistant to various tools and data sources using MCP servers. You can securely manage files, fetch web content, access Git repositories, and more within supported apps like Claude Desktop. Setup requires installing and configuring these servers, which provide your AI with safe, controlled access to useful resources.

Coding
Data
Files/PDF
Other
Web/Research

Use This MCP server To

Access and manage files securely from my AI assistant Fetch and summarize web pages for research Read and manipulate Git repositories Store and retrieve knowledge with persistent memory Perform time and timezone conversions Query databases like PostgreSQL through AI Automate multi-step problem solving with AI

README

Model Context Protocol servers

This repository is a collection of reference implementations for the Model Context Protocol (MCP), as well as references to community-built servers and additional resources.

Important

If you are looking for a list of MCP servers, you can browse published servers on the MCP Registry. The repository served by this README is dedicated to housing just the small number of reference servers maintained by the MCP steering group.

Warning

The servers in this repository are intended as reference implementations to demonstrate MCP features and SDK usage. They are meant to serve as educational examples for developers building their own MCP servers, not as production-ready solutions. Developers should evaluate their own security requirements and implement appropriate safeguards based on their specific threat model and use case.

The servers in this repository showcase the versatility and extensibility of MCP, demonstrating how it can be used to give Large Language Models (LLMs) secure, controlled access to tools and data sources. Typically, each MCP server is implemented with an MCP SDK:

🌟 Reference Servers

These servers aim to demonstrate MCP features and the official SDKs.

  • Everything - Reference / test server with prompts, resources, and tools.
  • Fetch - Web content fetching and conversion for efficient LLM usage.
  • Filesystem - Secure file operations with configurable access controls.
  • Git - Tools to read, search, and manipulate Git repositories.
  • Memory - Knowledge graph-based persistent memory system.
  • Sequential Thinking - Dynamic and reflective problem-solving through thought sequences.
  • Time - Time and timezone conversion capabilities.

Archived

The following reference servers are now archived and can be found at servers-archived.

  • AWS KB Retrieval - Retrieval from AWS Knowledge Base using Bedrock Agent Runtime.
  • Brave Search - Web and local search using Brave's Search API. Has been replaced by the official server.
  • EverArt - AI image generation using various models.
  • GitHub - Repository management, file operations, and GitHub API integration.
  • GitLab - GitLab API, enabling project management.
  • Google Drive - File access and search capabilities for Google Drive.
  • Google Maps - Location services, directions, and place details.
  • PostgreSQL - Read-only database access with schema inspection.
  • Puppeteer - Browser automation and web scraping.
  • Redis - Interact with Redis key-value stores.
  • Sentry - Retrieving and analyzing issues from Sentry.io.
  • Slack - Channel management and messaging capabilities. Now maintained by Zencoder
  • SQLite - Database interaction and business intelligence capabilities.

🚀 Getting Started

Using MCP Servers in this Repository

TypeScript-based servers in this repository can be used directly with npx.

For example, this will start the Memory server:

npx -y @modelcontextprotocol/server-memory

Python-based servers in this repository can be used directly with uvx or pip. uvx is recommended for ease of use and setup.

For example, this will start the Git server:

# With uvx
uvx mcp-server-git

# With pip
pip install mcp-server-git
python -m mcp_server_git

Follow these instructions to install uv / uvx and these to install pip.

Using an MCP Client

However, running a server on its own isn't very useful, and should instead be configured into an MCP client. For example, here's the Claude Desktop configuration to use the above server:

{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-memory"]
    }
  }
}

On Windows, wrap npx with cmd /c:

{
  "mcpServers": {
    "memory": {
      "command": "cmd",
      "args": ["/c", "npx", "-y", "@modelcontextprotocol/server-memory"]
    }
  }
}

Additional examples of using the Claude Desktop as an MCP client might look like:

{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem", "/path/to/allowed/files"]
    },
    "git": {
      "command": "uvx",
      "args": ["mcp-server-git", "--repository", "path/to/git/repo"]
    },
    "github": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-github"],
      "env": {
        "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
      }
    },
    "postgres": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-postgres", "postgresql://localhost/mydb"]
    }
  }
}

On Windows, apply the same wrapper to each npx-based entry above by changing "command" to "cmd" and prepending "/c", "npx" to the existing args. Leave uvx entries unchanged.

🛠️ Creating Your Own Server

Interested in creating your own MCP server? Visit the official documentation at modelcontextprotocol.io for comprehensive guides, best practices, and technical details on implementing MCP servers.

📚 Learn More

See ADDITIONAL.md for a curated list of frameworks and resources that simplify building MCP servers and clients.

🤝 Contributing

See CONTRIBUTING.md for information about contributing to this repository.

📦 Releasing

See RELEASING.md for how packages are published (OIDC trusted publishing from CI — no registry tokens) and how to retry a failed publish.

🔒 Security

See SECURITY.md for reporting security vulnerabilities.

📜 License

This project is licensed under the Apache License, Version 2.0 for new contributions, with existing code under MIT - see the LICENSE file for details.

💬 Community

⭐ Support

If you find MCP servers useful, please consider starring the repository and contributing new servers or improvements!


Managed by Anthropic, but built together with the community. The Model Context Protocol is open source and we encourage everyone to contribute their own servers and improvements!

servers FAQ

Can I use this to access and manage files securely?
Yes — the MCP servers include a Filesystem server that lets your AI securely read and write files with controlled access.
Can I use this to fetch and summarize web content?
Yes — the Fetch server fetches web pages and converts them for your AI to use efficiently.
Which apps support these MCP servers?
Claude Desktop supports these servers directly; other MCP clients may also work if configured.
Do I need an API key or account to use these servers?
Yes — some servers require API keys or tokens, such as GitHub or PostgreSQL servers.
How hard is it to set up these servers?
Setup is developer-level; it involves installing packages and configuring commands in your MCP client.
Can I use these servers with OpenAI, Claude, or Gemini models?
Yes — MCP servers are provider-agnostic and work with various LLMs including OpenAI, Claude, and Gemini.