NHL Go
Provides a Go-based NHL API client, command-line interface, and Model Context Protocol server for accessing NHL data.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Provides a Go-based NHL API client, command-line interface, and Model Context Protocol server for accessing NHL data.
Provides a context-augmentation layer to equip AI agents, especially coding agents, with an up-to-date knowledge base, significantly boosting their performance.
Integrates Nia's codebase understanding capabilities with MCP-compatible clients through function calling.
Enables AI agents to interface with and control N.I.N.A. (Nighttime Imaging 'N' Astronomy) software for astrophotography setups.
Implements a lightweight and fast server for the Model Context Protocol (MCP), leveraging streamable HTTP and the Nitro framework.
Provides a server-side interface for running and managing Nmap scans.
Connects web-based LLM chat APIs with local nmstate tools via an MCP server, enabling network configuration management.
Provides access to the NOAA Tides and Currents API for retrieving real-time and historical data, tide predictions, currents, meteorological data, and sun/moon information.
Provides a modular REST API for calculating various medical scores and indices, designed for integration with large language models.
Provides a foundational template for building Model Context Protocol (MCP) servers with Node.js.
Provides API documentation for Node.js projects when used with tools like Claude Desktop and Cursor AI.
Provides an easy-to-extend and robust template for creating and hosting stateful servers with Streamable-http transport using Node.js.
Manages NodeMCU devices through a REST API, WebSocket interface, and Model Context Protocol (MCP).
Enables AI clients to leverage the NoLang API for real-time AI-powered video generation.
Enables natural language interactive control of Universal Robots through an intelligent middleware system integrating large language models.
Enables Large Language Models (LLMs) to interact with the Norman Finance API, providing access to accounting, invoices, companies, clients, taxes, and more.
Provides an MCP server to integrate with the NOSIBLE search API.
Enables Claude to execute code snippets from the Nostr network.
Retrieves articles and user content from the note.com platform via API calls.
Exposes functions within a notebook environment through a REST API.
Automates professional interactions with Google NotebookLM by providing a Model Context Protocol (MCP) server.
Offers a versatile API server for the MCP protocol, compatible with various tools including the Joplin plugin NoteLLM.
Quickly record notes from the command-line, organized as Markdown files with YAML frontmatter, and interact with AI assistants via the Model Context Protocol.
Sends webhook notifications upon AI agent task completion, facilitating efficient multi-project development.
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.