Selector AI
Implements the Model Context Protocol (MCP) for Selector AI, providing a streaming-capable server and interactive client.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Implements the Model Context Protocol (MCP) for Selector AI, providing a streaming-capable server and interactive client.
Enables large language models or external tools to interact with a browser through a standardized Model Context Protocol for automation.
Autonomously learns from interactions to optimize AI agent performance and continuously improves its knowledge base through machine learning techniques.
Orchestrates interactions between users, large language models, and a suite of tools for automation and information retrieval.
Retrieves Sentry issue details or lists of issues for analysis and debugging.
Enables AI assistants to interact with serial devices for embedded systems, IoT, and hardware debugging.
Streamlines domestic and recurrent tasks efficiently through a customizable home automation platform.
Run and serve deep learning models with shell execution and containerization options.
Provides weather querying capabilities to agents within a Model Context Protocol (MCP) server environment.
Creates specialized servers for various use cases using CAMEL AI.
Extends the capabilities of AI assistants by providing specialized interfaces to interact with large language models (LLMs).
Automates San Francisco tennis court bookings on recreation websites through browser automation.
Provides comprehensive access to Salesforce B2C Commerce Cloud development features, enabling AI agents to assist with SFCC development tasks.
Connects Salesforce Marketing Cloud to the Model Context Protocol, enabling modular interactions for automation and advanced workflows.
Enables remote, programmatic, or containerized execution of shadcn CLI commands via an MCP server.
Provides a secure, local environment for AI agents to develop, compile, and run GPU shaders using Vulkan.
Integrates Shaka Packager with Claude AI applications, enabling video transcoding, packaging, and analysis.
Provides a comprehensive Model Context Protocol server implementation for Claude Code, leveraging an innovative multi-agent collaborative system.
Enables AI assistants to share and utilize a common knowledge base for Retrieval Augmented Generation (RAG).
Enables AI agents to parse, transform, and modify various spreadsheet file formats through a Model Context Protocol (MCP) server.
Executes shell commands via the Model Context Protocol (MCP) enabling safe execution of shell commands by AI agents.
Buy and manage domains through a Model Context Protocol (MCP) server.
Enables AI models to find the best online shopping deals by browsing multiple e-commerce websites and regions.
Connects Claude to your macOS Shortcuts library, enabling AI-driven execution and discovery of workflows.
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.