Firecrawl
Integrates powerful web scraping and content extraction capabilities into LLM clients like Cursor and Claude.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Integrates powerful web scraping and content extraction capabilities into LLM clients like Cursor and Claude.
Build AI-powered applications with this open-source framework for Node.js and Go.
Enables Large Language Models (LLMs) to autonomously reverse engineer applications by exposing Ghidra's core functionality through an Model Context Protocol (MCP) server.
Empowers AI agents with autonomous offensive cybersecurity capabilities by integrating over 70 professional security tools.
Provides an AI-native API gateway for cloud-native applications, extending Envoy and Istio with Wasm plugins.
Provides an all-in-one, intelligent automation testing solution for API, UI, and performance testing across multiple platforms.
Enables vibe reversing in IDA Pro through a Model Context Protocol server.
Compares and patches JavaScript objects, generating compact deltas for efficient updates and reversions.
Build and deploy open-source Model Context Protocols (MCPs) on Slack, Discord, and the web.
Enables building LLM-powered applications through a multi-agent programming paradigm.
Generate modern UI components instantly from natural language descriptions within your IDE.
Exposes any MCP tool as an OpenAPI-compatible HTTP server.
Provides access to large language and vision-language models based on linear attention for various natural language and multimodal tasks.
Collects, stores, distributes, and shares cybersecurity indicators and threats.
Defines a specification and schema for the Model Context Protocol.
Implements a Model Context Protocol (MCP) server for the Notion API, enabling AI-driven interaction with Notion content.
Provides an open-source, cloud-native LLMOps platform for designing, deploying, observing, and managing AI applications.
Automates browsers and APIs, enabling Large Language Models (LLMs) to interact with web pages for tasks like screenshot capture and JavaScript execution.
Provides a self-hosted web interface and API for interacting with large language models via llama.cpp.
Extracts text and metadata from web pages and online resources, offering various output formats.
Enables integration between WhatsApp and Large Language Models via the Model Context Protocol (MCP).
Provides a programmatic interface to automate content publishing, feed retrieval, and search functionalities on Xiaohongshu.com.
Retrieves transcripts and subtitles from YouTube videos, including automatically generated ones, without requiring an API key or headless browser.
Automates interactions with Twitter, including scraping data, sending tweets, and engaging with Grok AI, all without needing the official Twitter API.
MCP (Model Context Protocol) servers are tools that connect AI assistants like Claude, Cursor, and other AI coding tools to external data sources, APIs, and services. They enable AI models to access real-time information, execute code, interact with databases, and perform actions beyond their base capabilities. Check out our curated collection of the best MCP servers for Cursor →
MCP servers act as intermediaries between AI assistants and external systems. When you ask Claude or Cursor to perform a task requiring external data, the MCP server handles the request, fetches the data, and returns it in a format the AI can understand and use.
When selecting an MCP server, consider:
For detailed setup guides, see our Complete MCP Server Setup Guide →
Everything you need to know about installing, using, and troubleshooting Model Context Protocol.
To install MCP servers in Cursor: 1) Open Cursor settings (Cmd+,), 2) Navigate to MCP Servers section, 3) Click 'Add Server', 4) Enter server configuration (name and command), 5) Restart Cursor. Check out our curated collection of the best MCP servers for Cursor with detailed setup guides.
MCP servers are protocol-level integrations that work across multiple AI assistants (Claude, Cursor, etc.), while VS Code extensions are editor-specific. MCP servers provide context to AI models, whereas extensions add IDE functionality. MCP is more portable and AI-focused.
Most MCP servers listed are open-source and free. Some enterprise connectors (like Salesforce or Jira) may require paid API access to the underlying service, but the MCP server code itself is usually free.
Yes! The Model Context Protocol is open standard. You can build servers in Python or TypeScript/Node.js to expose your own internal APIs or databases to Claude and Cursor.
An MCP server is a lightweight program that exposes specific capabilities (data access, tool execution, prompts) to AI assistants through a standardized protocol. MCP servers allow Claude and other AI models to securely interact with external systems like databases, APIs, file systems, and web services while maintaining security boundaries.
MCP servers connect to Claude Desktop or other MCP-compatible clients through a standardized JSON-RPC protocol. When you configure an MCP server in Claude Desktop, Claude can access its resources (data/content), use its tools (functions to execute), and leverage its prompts (templated interactions). The protocol ensures secure, controlled access to external capabilities.
Essential MCP servers for beginners include: Filesystem (local file access), SQLite/PostgreSQL (database queries), GitHub (repository access), Brave Search (web search), and Memory (persistent context). These cover common use cases and have excellent documentation. Start with 2-3 servers and expand based on your needs.
Most MCP servers install via npm (npx) or Python (uvx/pip). Configure them in Claude Desktop's config file (claude_desktop_config.json) by specifying the command, arguments, and any required environment variables like API keys. Our directory links to each server's documentation with specific installation instructions.
MCP servers run locally on your machine with explicit permissions you configure. They can only access resources you authorize, and Claude cannot bypass these boundaries. However, always review server code, use official/verified servers when possible, limit permissions to what's necessary, and be cautious with servers that request broad access.
Resources are data sources Claude can read (files, database results, API responses). Tools are functions Claude can execute (run queries, send messages, create files). Prompts are pre-defined templates for common interactions. Most MCP servers expose one or more of these capability types.
MCP is supported by Claude Desktop (official), Cursor IDE, Continue (VS Code extension), and various community implementations. The protocol is open, so support is expanding to more AI development tools. Check our compatibility filters to find servers tested with your preferred client.
Our MCP servers directory is updated weekly with new servers, documentation improvements, and compatibility updates. We monitor GitHub releases, community contributions, and Anthropic announcements to ensure our listings reflect the latest MCP ecosystem developments.