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

92

Tools

343

Categories

11

Contributors

79

5 servers

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Figma MCP ServerFigma

Official Figma MCP server that brings design context directly into AI coding workflows. Provides tools for extracting design information, generating code from Figma selections, taking screenshots, creating and editing Figma files, generating diagrams from Mermaid syntax, searching design systems, managing Code Connect mappings, and uploading assets. Supports both remote (OAuth) and local (desktop app) server modes.

5.2k
Fetch MCP ServerAnthropic

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.

86.2k
Context7 MCP ServerUpstash

Provides up-to-date, version-specific documentation and code examples for libraries, frameworks, and SDKs directly into your AI prompts. Instead of relying on potentially outdated training data, Context7 fetches current documentation from the source. Supports thousands of libraries including React, Next.js, Node.js, Python packages, and more.

56k
Stripe MCP ServerStripe

Official MCP server for the Stripe API. Enables AI agents to interact with Stripe's payment infrastructure including creating and managing customers, payment intents, subscriptions, invoices, and products. Supports reading transaction data, handling refunds, and querying balance information. Useful for building payment integrations, debugging billing issues, and automating financial operations.

2.9k
E2B MCP ServerE2B

E2B's MCP server gives AI agents the ability to run arbitrary code in secure, isolated cloud sandboxes. Each sandbox is a fast-booting micro-VM where models can execute Python and shell commands, install packages, read and write files, and capture stdout/stderr — ideal for code interpretation, data analysis, and agentic workflows that need real execution.

0

Skills vs MCP servers

what's the difference?

Skillsthe “what to do”

A skillA reusable, structured prompt/workflow with recommended models, an example prompt, and compatible tools. packages know-how — instructions, an example promptA ready-to-use prompt template that demonstrates how to invoke the skill., and recommended models — so an agent performs a task consistently. Skills add knowledge, not new connections.

MCP serversthe “how to connect”

An MCP serverModel Context Protocol server — a standard way to expose tools, resources, and prompts to AI agents and IDEs. gives an agent new capabilities by connecting it to real systems (databases, APIs, files) over a transportHow the client talks to the server: stdio (local process), SSE, or HTTP streaming.. 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.

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