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
206
Tools
545
Categories
11
Contributors
182
Official Zapier MCP server that exposes thousands of app integrations and Zap actions to AI agents through a single remote endpoint. Lets agents trigger automations and perform actions across apps like Gmail, Slack, Google Sheets, and Salesforce without building custom integrations, with per-action scoping configured in the Zapier dashboard.
Official Expo MCP server that connects AI coding assistants to Expo projects and EAS services. Enables searching and reading Expo documentation, managing EAS builds and workflows, installing compatible libraries, inspecting TestFlight crashes and feedback, and automating visual verification through simulator screenshots and interactions. Supports both remote server capabilities and local development server features for advanced automation.
GitHub's official MCP Server that connects AI tools directly to GitHub's platform. Enables AI agents to manage repositories, issues, pull requests, branches, files, actions workflows, and code security. Supports both remote (OAuth) and local (Docker/binary) modes with fine-grained toolset configuration.
Official PayPal MCP server for commerce and payments. Lets AI agents create and capture orders, issue invoices, process refunds, manage subscriptions, and query transactions and disputes via the PayPal APIs. Useful for building checkout integrations, automating billing, and reconciling payments from an AI assistant.
Official Elastic MCP server that connects AI agents to Elasticsearch data using the Model Context Protocol. Enables natural language interactions with Elasticsearch indices — querying, analyzing, and retrieving data without custom APIs. Supports both stdio and streamable-HTTP transports, and works with Elasticsearch 8.x/9.x clusters including Elasticsearch Serverless. Distributed as a Docker container image from the Elastic registry.
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.