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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.

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.