AI Prompts
Collects and shares AI prompts, best practices, and curated rules to enhance developer workflows within AI-assisted coding tools.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Collects and shares AI prompts, best practices, and curated rules to enhance developer workflows within AI-assisted coding tools.
Provides an intuitive, tool-integrated AI chat interface for seamless interaction with external services and custom workflows.
Facilitates client-side consumption of Cloudflare's AI offerings through a monorepo of packages and demo applications.
Automates debugging for AI coding agents by running parallel investigations and validating fixes.
Manage Docker containers using natural language commands.
Integrates AI models into Ruby applications via the Model Context Protocol.
Enables AI assistants to interact with the Godot game engine by launching the editor, running projects, and capturing debug output.
Streamlines the creation of MCP server applications using a simple Python framework.
Integrates Google Workspace services with AI assistants and applications via the Model Context Protocol.
Connects your macOS digital life with AI, providing access to Messages, Contacts, Calendar, Location, Reminders, and Weather.
Proxies requests from a client to JetBrains IDEs such as IntelliJ, PyCharm, WebStorm, and Android Studio.
Provides a unified interface to multiple Large Language Model (LLM) providers, simplifying interaction with services like OpenAI, Anthropic, and Google Gemini.
Simplifies Kubernetes cluster management with an AI-powered, lightweight dashboard featuring multi-cluster support and intelligent analysis.
Enables persistent memory for Claude AI by leveraging a local knowledge graph to store and retrieve information.
Enables AI assistants to interact with Kubernetes clusters through natural language via the Model Context Protocol (MCP).
Enables local, private, and secured AI experimentation directly on your personal computer.
Enables AI assistants to create, read, and manipulate Microsoft Word documents through a standardized interface.
Automates FinOps processes to reduce cloud costs and streamline financial operations through no-code workflows.
Converts ComfyUI workflows into MCP tools to enable multimodal AI-generated content solutions powered by LLMs.
Bridges large language models and AI agents with physical robots, translating natural language commands into ROS/ROS2 instructions without code changes.
Provides example applications demonstrating the use of the Spring AI project.
Enables AI models to analyze Windows crash dumps by bridging LLMs with WinDBG/CDB.
Connects Large Language Models to Adobe Photoshop and Premiere Pro via the MCP protocol, enabling AI-driven control and automation.
Integrates ClickUp task management with AI applications through the Model Context 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.