System Info
Delivers real-time system metrics including CPU, memory, disk, network, and process information through a standardized Model Context Protocol interface.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Delivers real-time system metrics including CPU, memory, disk, network, and process information through a standardized Model Context Protocol interface.
Provides Claude with real-time system monitoring capabilities.
Enables MCP-capable applications to access, manage, and analyze system core dumps.
Orchestrates system updates, application installations, and performance optimizations across diverse operating systems, enabling agentic AI integration for intelligent management.
Provides access to the Tabnews API through the Model Context Protocol (MCP).
Connects to Typesense collections and retrieves data using an MCP client.
Provides a secure and comprehensive Model Context Protocol (MCP) server for managing file system operations, designed for integration with AI assistants like Claude Desktop.
Augments locally served LLMs with web search capabilities, URL text fetching, and page link extraction.
Connects AI assistants to the TailorKit API, enabling them to manage customizable product templates for e-commerce platforms.
Integrates TAK Server with AI systems to provide geospatial-aware deep research and analysis capabilities.
Enables Large Language Models to interact with Metabase for advanced data analysis, visualization, and dashboard management.
Enables AI agents to access and interact with DAO governance data from the Tally API.
Provides a Model Context Protocol (MCP) server implementation for fetching data from Talos nodes.
Serves Tambo documentation via a Model Context Protocol (MCP) server, enabling seamless integration with AI-powered development environments.
Facilitates communication with a Tapd server using either STDIO or SSE.
Connect large language models to Taroify for direct retrieval of component and API data from documentation.
Manages and executes tasks in a queue-based system using Cloudflare Workers.
Manage and track goals with hierarchical tasks within an MCP environment.
Automates task management in Linear and time tracking in TrackingTime through natural language.
Enables real-time user feedback for AI agents during development, ensuring continuous guidance and efficient iteration.
Enables management of tasks within Taskwarrior through an MCP (Most Common Protocol) server.
Provides access to Tatum's comprehensive blockchain API, supporting over 130 networks and 59 tools across multiple feature categories.
Enables AI-powered web searches via Tavily's API with added HTTP/HTTPS proxy support for enhanced LLM capabilities.
Facilitates AI agent communication and collaboration through a server-sent events (SSE) based system.
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.