Automation
Enables AI models to control macOS with mouse, keyboard, screen, and window management.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Enables AI models to control macOS with mouse, keyboard, screen, and window management.
Enables AI assistants like Claude to interact with and manage AWS resources using natural language.
Provides a versatile chat interface that supports various AI model providers and integrates external tools via Model Context Protocol.
Automates and simplifies diverse research workflows by integrating large language models with web search, social media, mapping, and code exploration.
Enables natural language control of DaVinci Resolve through AI coding assistants.
Provides a secure, efficient, and personalized local AI chat application experience.
Enables AI agents to interact with multiple EVM-compatible networks through a unified interface.
Automates the creation and validation of FedRAMP Security Authorization Packages using NIST's OSCAL standard.
Connects Model Context Protocol (MCP) servers to OpenAI-compatible LLMs.
Provides AI assistants with real-time access to NixOS packages, system options, Home Manager settings, and nix-darwin macOS configurations.
Connects IoT devices to AI Large Language Models by translating MCP protocol to MQTT, enabling natural language control of hardware.
Provides structured memory persistence for AI models via a knowledge graph server utilizing the Model Context Protocol (MCP).
Bridges large language models with the Metasploit Framework, enabling AI assistants to control security testing workflows via natural language.
Provides an MCP server for programmatically managing n8n workflows.
Enables Obsidian to integrate with AI applications through the Model Context Protocol.
Provides a local, open-source coding assistant experience similar to Claude Code, leveraging the Vercel AI SDK.
Provides an AI-first development framework that uses the Model Context Protocol (MCP) to enable Large Language Models (LLMs) to interact with development tools and context.
Enables Large Language Models to interact with Rails projects through the Model Context Protocol.
Prototype intelligent assistants, agents, and multi-agentic systems with a versatile and cohesive interface.
Facilitates spec-driven development workflows by providing structured prompts for generating requirements, design documents, and code.
Enables decoupled agent-tool interaction by providing a working pattern for Server-Sent Events (SSE) based Model Context Protocol (MCP) clients and servers.
Enables AI assistants to manage and operate Terraform environments through the Model Context Protocol (MCP).
Integrates AI-driven automation into Blender and Unreal Engine 5 (UE5) workflows for game level creation.
Integrates cutting-edge LLM/GenAI models into Unreal Engine for game development and interactive experiences.
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.