HorizonDataWave
Provides comprehensive access to LinkedIn data and functionalities, enabling data retrieval and user account management via the HorizonDataWave API.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Provides comprehensive access to LinkedIn data and functionalities, enabling data retrieval and user account management via the HorizonDataWave API.
Enables natural language interaction with Apache Iceberg lakehouses through a Model Context Protocol (MCP) server.
Generates images from text prompts using the Replicate Flux model.
Facilitates interaction with the Inkdrop note-taking application's local data via the Model Context Protocol.
Provides a lightweight and secure Python code execution sandbox based on IPython and Docker, designed for AI agents.
Enables access to Joplin notes through the Model Context Protocol for integration with AI assistants.
Integrates the Kagi Search API as a Model Context Protocol server.
Dynamically routes coding tasks between local LLMs, free APIs, and paid APIs to optimize costs.
Simplifies authorization for Python Model Context Protocol (MCP) servers.
Exposes Clojure REPL functionality over an SSE transport using the Model-Channel Protocol.
Manages and interacts with mobile devices and simulators for iOS and Android development.
Visualize configurations, manage HTTP(S) proxies, and mock data for frontend development services within webpack and Vite projects.
Integrates Naver Search and DataLab APIs for comprehensive searching and trend analysis across Naver services.
Provides contextual information about a Netbird network to applications supporting the Model Context Protocol (MCP).
Enables AI agents to send real-time notifications to devices via ntfy, supporting both public and self-hosted instances with token authentication.
Enables AI assistants to search for book and author information from the Internet Archive's Open Library.
Demonstrates Model Context Protocol (MCP) integration with Pokemon data through a client, server, and HTTP interface.
Provides access to prediction market data through the PolyMarket API.
Translates PowerPoint presentations using Amazon Bedrock models, preserving original formatting and structure.
Provides a local server that unifies and makes instantly searchable the latest documentation for various Python dependency managers directly within your agentic IDE.
Provides a minimal Rails API template for building Model Context Protocol (MCP) servers with tool execution capabilities.
Enables language models to leverage AI-powered web scraping capabilities with enterprise-grade reliability.
Provides a Model Context Protocol (MCP) server that integrates with Stripe for secure payment processing, customer management, and refund handling.
Enables language models to perform symbolic mathematics and computer algebra through tool-calling.
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.