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Centralizes Model Context Protocol (MCP) servers to enhance AI capabilities.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Centralizes Model Context Protocol (MCP) servers to enhance AI capabilities.
Provides AI agents with useful context to integrate Arcjet into applications and retrieve information about processed requests.
Executes Argo Workflows via a lightweight JSON-RPC interface.
Enhances GitOps continuous delivery for Kubernetes environments using Model Context Protocol and Generative AI.
Enables AI models to interact with the Art Institute of Chicago Collection through natural language, making artworks available as a Resource.
Provides a professional academic literature search server, integrating seamlessly with AI assistants to enhance research workflows.
Provides a scriptable desktop chat application for interacting with various Large Language Models (LLMs).
Provides a user confirmation interface for AI assistants through a personal terminal endpoint.
Enables Claude to generate images using OpenAI's `gpt-image-1` model.
Provides AI agents with access to Astro documentation for assisting users with Astro-related tasks.
Enables AI assistants to perform professional astronomical queries by providing integrated access to a wide range of astronomical data through the astroquery-cli tool.
Generates precise geometric images from Asymptote code, enabling AI models to request image creation.
Enables AI agents to manage and track asynchronous background timer operations.
Enables Model Context Protocol (MCP) clients to interact with the IQ AI Agent Tokenization Platform (ATP).
Enables LLM agents to interact with Aucterra's document classification and extraction services.
Enables AI assistants like Claude to interact with your computer's audio system for recording and playback.
Integrates the Augment Code CLI as a coding agent, providing tools for repository Q&A and automated code implementation within AI development environments.
Offers a high-performance Model Context Protocol (MCP) server for Australian postcode and suburb data, featuring intelligent fuzzy matching and AI-optimized capabilities.
Enables web-based intelligent agents to interact with MCP Servers via stdio and HTTP Server-Sent Events (SSE).
Provides AI assistants with contextual, version-specific documentation for Python project dependencies, eliminating manual package lookup and enhancing coding assistance.
Automatically generates documentation, test plans, and code reviews for code repositories using AI.
Automates VLSI chip design flows, transforming natural language instructions into complete RTL-to-GDSII sequences via AI-powered orchestration and microservices.
Integrates AI capabilities with the n8n automation platform through workflow configurations.
Enables AI assistants to access Automatisch workflow automation capabilities through 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.