Advocu
Enables Google Developer Experts to report their activities to the Advocu GDE API through AI-powered conversational interfaces.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Enables Google Developer Experts to report their activities to the Advocu GDE API through AI-powered conversational interfaces.
Implements government-grade security controls for software development, ensuring compliance and data protection.
Retrieves historical climate and meteorological data from the AEMET API for use with MCP-compatible clients.
Searches for papers from the American Economic Association (AEA) using Large Language Models (LLMs).
Automates decentralized exchange operations on Aerodrome Finance for the Base chain.
Provides a low-latency, clustered key-value store with HTTP and WebSocket interfaces, designed for cloud-native deployment.
Offers a comprehensive API and server for aerospace research, flight planning, and advanced orbital mechanics calculations.
Integrates with the Africastalking API for SMS functionality.
Facilitates airtime transfers to mobile numbers via the Africa's Talking API.
Generates dynamic, structured UI templates from natural language requests using Large Language Models and an MCP server.
Facilitates multi-agent conversations based on a specified OpenAPI specification.
Enables communication and coordination between different language model modes and roles across multiple systems.
Retrieves requirement and defect data from the TAPD platform to support AI client applications.
Connect agents, tools, and humans by leveraging Redis Streams and the Model Context Protocol (MCP) as a durable communication bus.
Enables secure communication and data exchange between AI agents within the AgentCraft framework.
Orchestrates and manages intelligent agents through a multi-agent platform with a dedicated web UI and MCP server.
Orchestrates intelligent business services using an agent-based architecture with Model Control Protocol (MCP) communication.
Empower AI chatbots with sophisticated long-term memory, comprehensive Notion workspace integration, and standardized tool communication via Model Context Protocol.
Powers an end-to-end voice and natural language product search with an AI chat assistant.
Facilitates the discovery of websites and APIs for seamless interactions between AI agents.
Provides crucial observability and tracing data for debugging complex AI agent runs.
Facilitates rapid experimentation with AI agents through a multi-component system featuring A2A and MCP server integrations.
Consolidates and serves multiple Model Context Protocol (MCP) servers through a single Stdio or HTTP interface.
Provides persistent memory capabilities for AI systems, enabling true continuity of consciousness across conversations.
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.