Outline
Enables AI agents to manage documents, collections, and other entities programmatically through the Outline knowledge base platform.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Enables AI agents to manage documents, collections, and other entities programmatically through the Outline knowledge base platform.
Enables LLMs to interact with and manage bookmarks stored in Raindrop.io using the Model Context Protocol.
Enables AI models to explore, analyze, and interact with artworks and collections from the Rijksmuseum through natural language interactions.
Provides deep, semantic-level analysis of Swift codebases to AI models with compiler-grade accuracy, leveraging Apple's SourceKit-LSP.
Enables AI agents to manage multi-step tasks in a structured manner, including tracking progress and enabling user approval checkpoints.
Enables AI models to execute terminal commands on a host machine and retrieve the output.
Orchestrates and combines prompts and Model Context Protocol (MCP) servers into compound MCP prompting tools.
Analyze data and gain insights by connecting to various data sources and running SQL queries using an AI-powered data analysis/BI tool.
Enables federated connections between AI systems and various data sources through a standardized architecture.
Provides a comprehensive set of tools for AI-driven development workflows, including file system operations, code analysis, Git operations, code execution, and system information…
Establishes a lightweight bridge for AI agents to interact with and automate tasks on Android devices.
Automates mobile UI testing and assists development workflows with a comprehensive suite of tools.
Integrates Blender with local AI models to control 3D modeling tasks using natural language prompts.
Empowers AI assistants with programmatic access to Linux kernel tracing capabilities using bpftrace.
Enables AI assistants to interact with the ChatGPT desktop app on macOS using the Model Context Protocol (MCP).
Enables AI assistants to access and analyze Chess.com data through the Model Context Protocol.
Empower AI with rich, consistent personalities via a Big Five personality engine for Model Context Protocol-compatible applications.
Manages containerd CRI interfaces using the Rust Model Context Protocol (RMCP) library.
Enables AI assistants to interact with Coolify instances through natural language.
Provides an advanced Model Context Protocol (MCP) server for seamless access to Israeli Government Open Data via data.gov.il.
Provides AI assistants with real-time, up-to-date Flutter and Dart documentation, including comprehensive pub.dev package information.
Aggregates and filters Model Context Protocol (MCP) server tools, optimizing context usage and preventing naming conflicts for AI clients.
Enhance function-calling-enabled language models and agents with a robust collection of tools.
Enables programmatic Gmail access for sending and receiving emails without local credential or token setup.
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.