Superface
Enables the use of Superface tools via the Model Context Protocol.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Enables the use of Superface tools via the Model Context Protocol.
Enables semantic search over internal documentation using a local server with Retrieval-Augmented Generation (RAG).
Offers a powerful, drop-in replacement for the official Superthread MCP, providing extensive tools and CRUD operations built on Cloudflare Workers.
Exposes supOS open-api via the Model Context Protocol, enabling clients to query topic trees and details.
Enables Large Language Models to access and query live SurveyMonkey data using natural language through a Model Context Protocol server.
Enables language models to interact with SuzieQ network observability instances via its REST API.
Converts SVG icons into web fonts with CSS and TypeScript support.
Provides a Model Context Protocol (MCP) server for accessing SVG logos from the SVGL API.
Serves Swagger/OpenAPI specifications and Postman collections as strategic MCP tools, enabling AI agents to dynamically interact with APIs.
Provides intelligent discovery and search capabilities for Swagger/OpenAPI endpoints, enabling AI assistants to dynamically explore and interact with REST APIs.
Integrates Smithery with the SWAPI API to enable searching and listing Star Wars universe data.
Normalizes GraphQL, JSON-RPC 2.0, and Cap'n Proto requests into Model Context Protocol (MCP) format via a multi-protocol edge proxy.
Provides secure execution of SWI-Prolog queries and operations for tools-enabled LLMs and applications via a Model Context Protocol server.
Provides enterprise-grade analysis, architecture guidance, and performance optimization for Swift projects.
Provides a universal Model Context Protocol (MCP) server for accessing OpenAI's APIs and other compatible AI providers through a standardized interface.
Provides an example project for creating MCP servers using Swift.
Enables control of SwitchBot devices via a Model Context Protocol (MCP) server, allowing integration with AI assistants.
Connects Sybase IQ data to LLMs like Claude Desktop through a read-only Model Context Protocol (MCP) server.
Enables use of the Symbol blockchain's REST API as Model Context Protocol (MCP) tools.
Provides an MCP server for searching, reading, and inspecting codebase symbols.
Transforms raw text into interconnected knowledge graphs and autonomously generates insights through advanced pattern detection.
Enables users to search, visualize, and listen to information using a Google Search agent powered by Gemini models.
Connects Python applications to native operating system functionalities like clipboard management and URL handling.
Bridges native OS functionalities to Model Context Protocol (MCP) for clipboard management and URL handling.
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.