Discover The Best MCP Servers & Tools
Empowering LLMs with MCP Servers, find MCP servers for your needs.
Newly Released
Official
Community
What is MCP
The Model Context Protocol (MCP) serves as an open protocol designed to create seamless connections between LLM applications and their external data sources and tools. Whether you're developing an AI-powered IDE, enhancing a chat interface, or building custom AI workflows, MCP offers a standardized approach for LLMs to access and utilize the context they require.
MCP Server
The MCP Server repository features a comprehensive collection of reference implementations and community-contributed Model Context Protocol servers, illustrating the flexibility and expandability of the MCP. It demonstrates how these servers can be leveraged to provide Large Language Models (LLMs) with secure and controlled access to various tools and data sources.
The MCP servers in this collection are built using either the Typescript SDK or Python SDK, offering developers multiple implementation options.
Why we create the Hub?
We created the MCP Server Hub to address a growing need in the AI development community. As the Model Context Protocol continues to gain traction, server developers increasingly seek reliable and efficient MCP servers to enhance their LLM applications. Our server hub serves as a central server repository where developers can discover, evaluate, and implement the most suitable servers for their specific use cases.
The MCP Server Hub streamlines the process of finding and implementing MCP servers by providing a curated collection of both reference implementations and community contributions. We understand that choosing the right server is crucial for maximizing the potential of Large Language Models, whether you're building an AI-powered IDE, developing chat interfaces, or creating specialized AI workflows. Our platform helps developers make informed decisions by offering detailed documentation, implementation examples, and real-world use cases for each server.
Beyond being just a discovery platform, the MCP Server Hub fosters a collaborative ecosystem where developers can share their own MCP server implementations. This open approach encourages innovation and helps establish best practices within the community. Whether you're looking for a TypeScript-based MCP server for web applications or a Python MCP server for data science projects, our hub provides the resources and guidance needed to make your implementation successful.
The MCP Server Hub also serves as a vital feedback loop for the MCP ecosystem. As developers contribute their MCP servers and share their experiences, we collectively improve the protocol's implementation patterns and identify new opportunities for enhancement. This collaborative environment ensures that the MCP Server Hub remains a dynamic resource that evolves alongside the needs of the AI development community.
By creating this navigation platform for MCP servers, we're not just building a MCP server directory – establishing a foundation for the future of LLM integration. The MCP Server Hub empowers developers to leverage the full potential of Large Language Models while maintaining secure and controlled access to tools and data sources, ultimately accelerating the development of more sophisticated and capable AI applications.