MCP Servers
The open registry for Model Context Protocol servers. Find the right tools, resources, and prompts for your AI agents — filtered by category, transport, or use case.
Servers
175
Tools
465
Categories
11
Contributors
153
The official MCP reference and test server demonstrates tools, resources, prompts, sampling, and protocol capabilities for MCP client development.
Provides HTTP request capabilities through the Model Context Protocol. Enables AI agents to fetch web content, retrieve API responses, and download resources from URLs. Supports converting HTML to Markdown for easier consumption and can handle various content types including JSON, text, and binary data.
Apollo's official MCP server that exposes GraphQL operations as MCP tools, letting AI agents interact with any GraphQL API through the Model Context Protocol. Turns curated GraphQL operations into callable tools, supports schema introspection, and can run locally alongside a graph via the Rover CLI or in production with the Apollo Runtime Container.
Skills vs MCP servers
what’s the difference?Skillsthe “what to do”
A skill packages know-how — instructions, an example prompt, and recommended models — so an agent performs a task consistently. Skills add knowledge, not new connections.
MCP serversthe “how to connect”
An MCP server gives an agent new capabilities by connecting it to real systems (databases, APIs, files) over a transport. MCP adds connections and actions, not task instructions.
Rule of thumb: reach for a skill when you need the model to do a task well, and an MCP server when you need it to reach a tool or system. They compose — a skill can rely on tools an MCP server provides.
Built an MCP server?
Submit it to the registry — it’s open source and community-maintained.