System Monitor
Exposes system metrics via the Model Context Protocol (MCP), enabling LLMs to retrieve real-time system information.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Exposes system metrics via the Model Context Protocol (MCP), enabling LLMs to retrieve real-time system information.
Provides a ready-to-go starting point for building custom Model Context Protocol servers.
Exposes Twilio's APIs to AI assistants and other tools that support the Model Context Protocol (MCP).
Automates Unity project development by enabling AI to autonomously compile, test, debug, and manipulate projects through integration with AI coding assistants.
Connects a chat REPL to the Wolfram Alpha computational intelligence engine.
Enables interaction with WooCommerce stores through the WordPress REST API using JSON-RPC 2.0.
Automate complex Google Workspace tasks and simplify API authorization by integrating with Gemini CLI via a Google Apps Script-based MCP server.
MCP server enabling access to conversation history, prompt templates, and observability data.
A freemium MCP server for managing and testing AI agent interactions.
Enables seamless interaction with SAP ABAP systems for managing ABAP objects and streamlining development workflows.
Provides a comprehensive developer portal to extend and integrate with Anytype's unique offline-first knowledge management system.
Controls Apple Music on macOS using AppleScript through a FastMCP server implementation.
Provides a template for building Model Context Protocol (MCP) servers that connect AI assistants to external data sources.
Manage development tasks with AI assistance, from requirements parsing to implementation step generation.
Quickly scaffolds Model Context Protocol server and client applications using TypeScript and modern tooling.
Enables comprehensive social media and web data collection via a Model Context Protocol server.
Provides AI assistants with seamless access to Israeli Government Open Data for search, discovery, and analysis.
Provides a Metadata Change Proposal (MCP) server implementation for data governance.
Transforms a Dify application into an MCP server endpoint.
Empowers large language models with real-world visual perception through image object detection, localization, and captioning APIs.
Generates dynamic ECharts chart pages on demand via an MCP service.
Demonstrates an application exclusively accessible via the Model Context Protocol (MCP).
Enables natural language flight searches using Google's Gemini 2.5 Pro and the Model Context Protocol.
Extend Claude's capabilities by enabling it to write and use Python tools directly within conversations.
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.