Gemini Pro
Integrates Google's Gemini AI models with MCP-compatible clients like Claude Desktop, enabling access to advanced AI capabilities.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Integrates Google's Gemini AI models with MCP-compatible clients like Claude Desktop, enabling access to advanced AI capabilities.
Provides a Windows-compatible Model Context Protocol (MCP) server, enabling AI assistants to seamlessly interact with Google's Gemini CLI.
Provides a robust foundational structure for developing generative AI applications.
Enables AI models to control and interact with aircraft within the GeoFS flight simulator environment.
Facilitates testing and refining regex patterns against defined test cases with the assistance of Large Language Models.
Converts images into animated videos in the style of Ghibli using AI.
Automates the generation of personalized, high-quality diary entries using AI.
Integrates GIMP 3 with the Model Context Protocol, enabling external AI models and applications to remotely control the image manipulation program.
Automates git commits on behalf of AI, enabling tracking of AI contributions in a codebase.
Converts git repositories and local file paths into structured, LLM-ready prompt formats, providing context for AI models.
Investigates git repositories to provide detailed insights into history, branch relationships, and development patterns.
Automates common Git operations and GitHub interactions through a Model Context Protocol server.
Empowers AI models to perform Git operations and manage GitHub pull requests.
Enables AI assistants to manage Gitee Enterprise repositories, issues, and pull requests through the Model Context Protocol (MCP).
Enables triggering GitHub workflow dispatch events and retrieving information about GitHub Actions and releases.
Enables AI agents to securely access and manage GitHub Enterprise data, including users, organizations, and licenses.
Integrates GitHub project calendars with AI assistants for team management, workload analysis, and intelligent task assignment.
Enables natural-language interactions with GitHub repositories by bridging GitHub data with chat-based AI completion.
Manages and organizes GitHub issues for improved workflow.
Manages GitHub issues in a Kanban board format to streamline task management for LLMs.
Connects GitHub code to Claude.ai by extracting code from repositories using the Pera1 service.
Analyzes GitHub pull requests and manages issues as part of an automated workflow.
Enables AI assistants to browse and read files from GitHub repositories.
Automates the analysis of local Git repositories and the creation of new GitHub repositories for AI applications.
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.