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
Sanity's official MCP server that connects structured content to AI agents. Provides tools to run GROQ queries, read and write documents, explore and deploy schemas, manage content releases, and generate images, all with full schema context. Available as a hosted remote server at mcp.sanity.io and works with MCP-compatible clients like Cursor, Claude Code, and VS Code.
Webflow's official MCP server that connects AI tools to your Webflow projects via the Webflow Data API. Lets agents manage sites and pages, work with CMS collections and items, read form submissions, and publish changes, enabling content updates and site automation from an MCP-compatible client.
Zoom's official remote MCP server, published to the MCP registry, that gives AI agents access to Zoom capabilities over the Model Context Protocol. Supports semantic meeting search, Zoom-wide chat and docs search, meeting assets and recording resources, and Zoom Docs import/export, so assistants can find and summarize meeting content and manage related data. Authenticates via OAuth.
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.