Mc-Agent
Enables AI agents to interact with Minecraft Bedrock using WebSockets and the Minecraft Script API.
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 interact with Minecraft Bedrock using WebSockets and the Minecraft Script API.
Provides a generic Model Context Protocol framework for building AI-powered applications.
Enables command-line interaction with Anthropic's Claude model through Model Context Protocol servers.
Enables users to interact with LLMs and MCP-compatible servers from the command line.
Demonstrates a Model Context Protocol (MCP) client implementation using Web Workers and Server-Sent Events (SSE).
Facilitates interaction with an LLM-powered chatbot following the Model Context Protocol.
Connects to Ollama LLM backends and Model Context Protocol (MCP) servers to enable tool execution by LLMs.
Provides Elixir project and dependency documentation to an LLM through an SSE MCP server.
Provides a Go SDK for building Model Communication Protocol (MCP) tools and servers.
Provides an open protocol and comprehensive guide for connecting AI models to external data and tools.
Framework to simplify building, managing, and deploying Model Context Protocol (MCP) clients and servers.
Provides a unified interface for LLMs to interact with multiple IT Service Management (ITSM) systems.
Scaffold new Model Context Protocol (MCP) servers with provided tools and templates.
Enables seamless integration between Model Context Protocol (MCP) clients and servers by providing a Java-based implementation of the MCP mediator.
Provides a simple MCP server exposing a tool to retrieve current weather information for a given city using the Open-Meteo API.
Generates a variety of random data, including UUIDs, numbers, passwords, dice rolls, and card draws.
Converts JavaScript modules into sandboxed Model Context Protocol (MCP) servers with automatic reflection and type inference.
Retrieves and analyzes issues from Sentry.io or self-hosted Sentry instances using the Model Context Protocol.
Centralizes configurations and scripts for Model Context Protocol servers to integrate external tools with language models.
Centralizes the discovery, comparison, and implementation of Model Context Protocol (MCP) servers, ranked by community popularity.
Provides a curated collection of Model Context Protocol (MCP) servers.
Provides a modular and extensible framework for building Model Context Protocol servers.
Performs high-precision mathematical calculations directly within LM Studio using the Model Context Protocol.
Enables Rust projects to interact with external tools using the Model Context Protocol.
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.