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Aggregates and unifies multiple Model Context Protocol (MCP) servers, enabling middleware application and dynamic management.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Aggregates and unifies multiple Model Context Protocol (MCP) servers, enabling middleware application and dynamic management.
Enables collaboration between small, on-device LLMs and larger cloud-based models for cost-efficient language processing.
Provides a catalog of official Microsoft MCP server implementations for AI-powered data access and tool integration.
Build a comprehensive personal knowledge base with this open-source note-taking application.
Enables the development, deployment, and scaling of web browsing agents through a single API.
Provides a user interface for Nx and Lerna monorepos, enhancing developer workflow and AI integration within code editors.
Enables interaction with an Obsidian vault via the Obsidian Local REST API plugin.
Connects Claude Desktop to read and search your Obsidian vault's Markdown notes.
Facilitates communication with MCP servers by providing a LangGraph agent and a CopilotKit-powered frontend.
Connects to the Perplexity API, enabling real-time, web-wide search within the Model Context Protocol ecosystem.
Orchestrates components within a lightweight, high-performance rule engine framework for Go applications.
Provides AI assistants with comprehensive access to shadcn/ui v4 components, blocks, demos, and metadata via the Model Context Protocol.
Build Java enterprise applications with a restrained, efficient, open, and ecological framework.
Exposes MCP stdio-based servers over SSE or WebSockets, enabling remote access and integration.
Automates data integration via a stable, self-healing SDK, providing automated schema-drift detection, retries, and remappings to maintain continuous data flow without connector m…
Accelerate the development and research of complex Retrieval-Augmented Generation (RAG) systems with a low-code, modular framework.
Transforms existing API servers and services into Model Context Protocol (MCP) compliant endpoints with zero code changes.
Provides scalable, fast, and disk-friendly vector search capabilities directly within PostgreSQL.
Enables seamless integration between AI agents and the Windows operating system.
Enables AI agents to interact with and automate Xcode projects through the Model Context Protocol.
Establishes an open, standardized protocol for framework-agnostic agent communication.
Analyzes agentic systems to identify potential vulnerabilities and security insights.
Experiments with Azure API Management's AI capabilities, integrating with Azure OpenAI, AI Foundry, and more.
Provides a Python SDK for interacting with the AT Protocol (Bluesky).
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.