Personal Notes
Offers concise, topic-wise notes on machine learning, combining mathematical foundations, practical perspectives, and architectural overviews with diagrams.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Offers concise, topic-wise notes on machine learning, combining mathematical foundations, practical perspectives, and architectural overviews with diagrams.
Indexes and enables natural language querying of your Obsidian notes through a Retrieval-Augmented Generation (RAG) server.
Provides a simple Python implementation of a Model Communication Protocol (MCP) server over a network using Server-Sent Events (SSE).
Provides access to the Pexels API for searching and retrieving high-quality photos, videos, and collections.
Enables Large Language Models to interact with the Phabricator API through a Model Context Protocol (MCP) server.
Provides an interface to evaluate Smalltalk expressions and retrieve code and system metrics from a Pharo environment.
Facilitates communication with a local Pharo Smalltalk image via a local server.
Control Phillips Hue lights through natural language commands using the Model Context Protocol.
Enables querying Phoenix data from Claude Desktop through CData JDBC Drivers via a read-only Model Context Protocol (MCP) server.
Enables natural language interaction and control over a physical robot via a Model Context Protocol server.
Provides tools for enhancing and manipulating digital images.
Delivers current date and time via the MCP and HTTP protocols.
Manages inspirational phrases and integrates with Claude for Desktop and other Model Context Protocol (MCP) clients.
Provides a Model Context Protocol (MCP) server for interacting with the PI Dashboard API.
Manages local photos with AI features such as semantic search and face recognition.
Retrieves SVG icons quickly using natural language processing and the Iconify API.
Answers questions using Pieces Long-Term Memory within an MCP context.
Empower AI agents with customizable system prompts and a comprehensive suite of development and Git management tools.
Enables Claude to interact with public and private IPFS through the Pinata API for file and group management.
Provides Large Language Models with read-only access to Pinboard.in bookmarks for search, filtering, and retrieval.
Checks PineScript syntax using TradingView's official API.
Pings a specified host and returns the connectivity result.
Enables Large Language Models (LLMs) to query live PingOne data and interact with it using natural language through a standardized Model Context Protocol (MCP) interface.
Enables Large Language Models to query live Pinterest data through a Model Context Protocol server.
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.