AWorld
Facilitates the building, evaluation, and running of general multi-agent assistance systems.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Facilitates the building, evaluation, and running of general multi-agent assistance systems.
Integrates Azure DevOps capabilities directly into development environments by providing a local server that enables interaction with various services.
Provides a high-performance, resilient AI gateway for connecting to multiple large language model providers through a single, unified API.
Summarizes chat messages based on user queries.
Enables Claude to interact with the ChatGPT desktop application on macOS.
Enables Claude Code as a one-shot MCP server, allowing LLMs to directly leverage Claude's coding capabilities.
Builds a project-specific knowledge graph to supercharge AI assistants with context-aware Retrieval Augmented Generation (RAG) capabilities.
Provides a comprehensive context engineering infrastructure with unified Model Context Protocol (MCP) tools and secure integrations for AI agents.
Provides a curated directory for discovering Awesome MCP Servers.
Indexes and searches third-party library documentation using semantic splitting and vector embeddings.
Enables interaction with Text to Speech and audio processing APIs for MCP clients.
Enables AI assistants to manage Gmail through natural language interactions with auto authentication support.
Provides a comprehensive toolkit for AI agents to interact with blockchain and decentralized finance.
Integrates Google Calendar with Model Context Protocol, enabling LLMs to manage calendar events through a standardized interface.
Extends the capabilities of Model Context Protocol (MCP) applications with WebAssembly plugins.
Enables interaction with iOS simulators for tasks like UI inspection, UI interaction, and screenshot capture.
Enables interaction with Jupyter notebooks running in a local JupyterLab environment through the Model Context Protocol (MCP).
Provides a Model Context Protocol (MCP) server for managing Kubernetes and OpenShift resources.
Serves LangChain LLM applications and agents as robust FastAPI-powered API endpoints.
Facilitates the discovery and installation of MCP servers built for use with Cline.
Provides a framework to build Model Context Protocol servers in TypeScript.
Connects MCP clients that only support local (stdio) servers to a remote MCP server, enabling authentication support.
Connects MCP tools to the OpenAI API, enabling interaction with them through a compatible interface.
Exposes LLM documentation defined in llms.txt files to IDEs for improved context retrieval and auditability.
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.