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
Contentful's official MCP server for the Content Management API. Gives AI agents tools to create, edit, organize, and publish content, manage content models and assets, and work across spaces and environments. Useful for automating editorial workflows and content operations in a Contentful-backed headless CMS.
Payload CMS provides an MCP integration for agents to explore and manage CMS content, schemas, and application workflows.
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.
Reference MCP server for Git repository operations. Provides tools to read, search, and manipulate Git repositories including viewing commit history, diffs, branches, file contents at specific revisions, and repository status. Enables AI agents to understand code changes and navigate version history without direct filesystem access.
MCP server for Atlassian Bitbucket that connects AI tools to repositories, pull requests, branches, and pipelines. Enables agents to review and create pull requests, read file contents and diffs, leave comments, and inspect build status on Bitbucket Cloud and Server.
Directus' MCP integration connects agents to headless CMS data, schemas, and operations for governed content and application workflows.
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.
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.