Prompt Server
Provides preset prompt templates based on the Model Context Protocol (MCP) to streamline various tasks in editors like Cursor and Windsurf.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Provides preset prompt templates based on the Model Context Protocol (MCP) to streamline various tasks in editors like Cursor and Windsurf.
Enables AI interaction with Revit for data extraction, element manipulation, and code execution.
Connects Rhino 3D to AI Agents via the Model Context Protocol (MCP), enabling AI-assisted 3D modeling.
Enables complex problem-solving by leveraging a multi-agent system for deeper analysis and coordinated task execution.
Orchestrates access to OpenAI, Google Gemini, and Azure AI models through a unified Model Context Protocol (MCP) interface for enhanced coding workflows.
Exposes Visual Studio Code editing features to an LLM for AI-assisted coding.
Enables AI assistants to retrieve and interpret real-time weather data via the Model Context Protocol.
Enables access to blockchain interactions, swaps, staking, and crypto trading strategies for AI agents.
Enables AI assistants to execute AWS CLI commands in a secure, containerized environment using the Model Context Protocol (MCP).
Integrates with Azure AI Foundry to connect to existing Azure AI Agents, leveraging models and knowledge tools.
Provides a comprehensive React component library that integrates React Aria and Tailwind CSS for modern development workflows and AI-powered tooling.
Enables Claude Desktop to interact directly with Figma, allowing for AI-assisted design workflows.
Enables AI assistants to discover and utilize Model Context Protocol (MCP) services based on natural language queries.
Enables AI assistants to interact with Figma files through the ModelContextProtocol.
Connect Flutter applications with AI coding assistants via the Model Context Protocol.
Enables LLM assistants to interact with the Foundry ecosystem for Solidity development and blockchain analysis.
Enables AI assistants to interact with and manage Google Cloud Platform resources using natural language.
Enables AI assistants to interact with and control a Home Assistant instance using the Model Context Protocol.
Generates images from text prompts within the Cursor IDE by leveraging the Jimeng AI service.
Empowers AI assistants with image processing capabilities such as cropping, resizing, object detection, and OCR through an MCP server.
Securely executes Kubernetes commands from AI assistants like Claude by acting as a Model Context Protocol (MCP) server.
Generates logos using FAL AI, providing image generation, background removal, and automatic scaling.
Facilitates open-source intelligence by collecting user account information from various public sources.
Provides protocol-based memory management for AI to improve response accuracy, reduce drift, and stabilize context over long sessions.
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.