Enhanced Interactive Feedback
Establishes a robust interactive feedback server designed to improve communication and workflow for AI development tools.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Establishes a robust interactive feedback server designed to improve communication and workflow for AI development tools.
Integrates red-teaming, prompt auditing, and AI safety analysis into Model Context Protocol (MCP) compatible clients.
Facilitates interaction with OpenAI, Anthropic, and EnrichB2B services using the Model Context Protocol.
Enables interaction with the Ethereum Name Service (ENS) for resolving names, checking availability, and retrieving records.
Facilitates collaborative AI agent interaction by allowing them to share and reflect on each other's responses to the same prompt.
Facilitates collaborative debates between multiple AI agents, enabling them to discuss and reach consensus on user prompts.
Interacts with EPICS process variables (PVs) to retrieve values, set values, and fetch detailed information.
Integrates AI assistants with ERPNext/Frappe to manage data and facilitate comprehensive custom application development.
Deploys an MCP server on ESP32-C6 microcontrollers for remote interaction, integrating seamlessly with Warp terminal.
Delivers crypto ETF flow data to empower AI agents' decision-making.
Provides access to Etherscan blockchain data for LLM applications via the Model Context Protocol.
Provides AI assistants with multi-chain EVM blockchain data access, including balances, contracts, and gas prices.
Provides a Model Context Protocol (MCP) Everything server with SSE transport, containerized for easy deployment.
Enhances local LLMs with agentic capabilities, enabling autonomous tool creation and invocation.
Assists students in preparing for any exam or test by serving as an intelligent, AI-powered study companion.
Converts Excel and Apple Numbers files to PDF format, integrating with AI assistants.
Provides an Express.js-wrapped MCP server, enabling AI tools like Cursor to access real-time weather data and server information.
Provides a Model Context Protocol (MCP) server for seamless interaction with fal.ai's AI models and services.
Generates images from text prompts using fal.ai and integrates with AI IDEs.
Generates data pipeline code for any Airbyte Connector using a single natural language prompt.
Enables AI assistants like Claude to perform high-speed filesystem operations, manage Git repositories, and engage in interactive user prompts.
Provides real-time weather data for any city worldwide, integrating seamlessly with Claude Desktop, VS Code, and Cursor.
Provides an MCP server to integrate AI assistants with Fatebook for tracking personal predictions.
Facilitates browser automation by providing a robust bridge that communicates over `stdin/stdout` using a JSON-RPC-like protocol.
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.