Youtube Summarizer
Exposes YouTube summarization APIs as tools compatible with the MCP (Meta-Control Protocol).
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Exposes YouTube summarization APIs as tools compatible with the MCP (Meta-Control Protocol).
Extracts YouTube video transcripts through a versatile server supporting multiple transport protocols and formats.
Extracts transcripts from public YouTube videos for AI analysis and integration with tools like Cursor and Claude Desktop.
Extracts transcripts from YouTube videos via the command line.
Enables access to the YouTube Translate API for obtaining transcripts, translations, and summaries of YouTube videos.
Retrieves YouTube video URLs from a specified Watch Later playlist within a given timeframe.
Enables Claude to fetch and analyze YouTube video transcripts.
Enables LLMs to interact with YugabyteDB by listing tables, schema, row counts, and running read-only SQL queries.
Manages and retrieves textual memories using keyword detection and a flexible API.
Integrates OWASP ZAP with AI assistants and MCP clients to enable AI-powered security testing through automated vulnerability scanning.
Connects Figma designs to AI coding assistants in VS Code using the Model Context Protocol.
Provides natural language access to the Zapmail API for domain management, mailbox operations, and exports, enabling AI assistants to interact with Zapmail.
Empowers LLMs with Bitcoin Lightning Network payment capabilities via the ZBD API.
Enables conversational AI clients to analyze network traffic data using the Zeek network security monitoring engine.
Enables integration with Zendesk to manage and interact with tickets programmatically.
Automates publishing new Zenn articles from GitHub repositories using GitHub Actions.
Provides a search functionality for blog posts and generates content summaries in the style of Cybozu Frontend Weekly.
Exposes comprehensive financial data from Yahoo Finance, including stock insights, historical prices, and company information, for integration with AI tools.
Enables algorithmic trading with the Zerodha Kite API through an MCP server.
Enables real-time stock trading on Zerodha through natural language commands using LLMs.
Enables natural language interaction with product security findings within AI-assisted development tools.
Provides real-time access to Zillow real estate data, enabling property search, valuation, and market trend analysis.
Enables AI models to access and search ZIM format knowledge bases offline.
Provides Japanese postal code to address lookup functionality for AI assistants and other Model Context Protocol clients.
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.