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Provides a comprehensive set of tools for AI-driven development workflows, enabling AI to assist in software development tasks by accessing both local and remote resources.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Provides a comprehensive set of tools for AI-driven development workflows, enabling AI to assist in software development tasks by accessing both local and remote resources.
Integrates MCP Clients with Stability AI to generate, edit, and upscale images.
Automate web interactions to bypass advanced anti-bot systems, Cloudflare, and social media blocks for undetectable real-browser automation.
Provides a natural language interface for LLMs and AI agents to interact with the ThingsBoard IoT platform.
Enables structured reasoning in agentic AI workflows by providing a think tool for pausing and recording thoughts.
Implements a Model Context Protocol (MCP) server for Trino in Go, enabling AI assistants to interact with Trino's distributed SQL query engine.
Enables AI agents and assistants to interact with VS Code through the Model Context Protocol.
Provides Model Context Protocol (MCP) capability to Ruby on Rails applications, specifically as a server.
Automate Unity Editor operations and game development tasks using natural language commands via AI assistants.
Simplifies the creation of AI agents with TypeScript, offering modular architecture and multi-provider support.
Connects Claude desktop and other compatible AI assistants to Ahrefs data.
Integrates CircleCI with the Model Context Protocol to enable natural language interactions for development workflows.
Provides a collection of community-maintained servers compatible with the Model Context Protocol (MCP).
Brings AI-powered business intelligence to ERPNext with natural language queries.
Enables collaborative workflows for Goose agents through a Model Context Protocol (MCP) server and protocol.
Empowers AI coding assistants with persistent memory and learned coding patterns from your codebase.
Enables AI models to interact with and monitor JVM-based applications through a standardized Model Context Protocol (MCP) server implementation.
Connects AI agents to the Keboola platform for data access, transformation, and job management.
Enhances code quality by providing AI coding assistants with structured, prompt-based analysis for identifying and addressing common issues.
Discovers and recommends Model Context Protocol (MCP) servers via natural language queries to help AI assistants find relevant tools.
Enables AI assistants to interact with Metabase, providing access to data and analytical tools.
Queries multiple Ollama models and combines their responses to provide diverse AI perspectives on a single question.
Enables seamless AI-powered automation and multi-instance management for the Cursor editor by bridging it with Claude's desktop application and other Model Context Protocol (MCP)…
Manages and deploys AI persona teams, allowing users to summon or collaboratively engage specialized AI personalities for various analytical and creative tasks within MCP-compatib…
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.