Deep Dive Into AI
Provides educational resources for learning AI, machine learning, and deep learning using PyTorch and Apple's MLX frameworks.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Provides educational resources for learning AI, machine learning, and deep learning using PyTorch and Apple's MLX frameworks.
Provides a collection of official plugins for the Dify platform, including models, tools, agent strategies, and extensions.
Provides access to real-time and historical stock market data for AI assistants through the Model Context Protocol (MCP).
Enables interaction and automation of IDA Pro with Large Language Models via a Model Context Protocol server.
Provides access to your iTerm session for AI models, enabling them to execute commands and interact with the terminal.
Integrates JADX decompiler with Model Context Protocol (MCP) for AI-powered static code analysis and real-time reverse engineering.
Enables interaction with LinkedIn through AI assistants, allowing users to scrape profiles, companies, and jobs.
Executes AppleScript and JavaScript for Automation (JXA) scripts on macOS via a Model Context Protocol (MCP) server.
Provides a self-hosted registry and unified gateway for managing Model Context Protocol (MCP) servers and their tools for AI agents.
Provides long-term memory capabilities to AI agents through a Model Context Protocol (MCP) server.
Exposes AI tools, resources, and prompts from NestJS applications using the Model Context Protocol.
Facilitates advanced reverse engineering tasks by acting as a model-agnostic AI assistant within environments like Ghidra, leveraging a tool-driven approach.
Integrates security testing and penetration testing tools into AI workflows via the Model Context Protocol.
Installs and manages Model Context Protocol (MCP) servers, remaining client-agnostic.
Bridges WeChat Read data with AI clients like Claude Desktop, enabling seamless access to notes and reading data.
Exposes WordPress functionality through a standardized Model Context Protocol (MCP) interface for secure AI and application interaction.
Powers AI agents with a semantic engine for accessing business data with accuracy, context, and governance.
Downloads YouTube subtitles using yt-dlp and connects to claude.ai via Model Context Protocol.
Provides intelligent coding assistance through custom AI tools directly within Cursor's Composer.
Enables agentic AI workflows for developers using Docker containers and Markdown prompts.
Delegates AI coding tasks to Aider, enabling cost reduction and enhanced control over the coding model.
Enables AI systems to interact with Airtable bases for reading and writing data.
Automatically annotates papers using Large Language Models (LLMs) to provide contextual information while reading.
Enables AI models to control macOS with mouse, keyboard, screen, and window management.
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.