Notellm
Offers a versatile API server for the MCP protocol, compatible with various tools including the Joplin plugin NoteLLM.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
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.
Automate expense tracking, run smart financial queries, and integrate real financial data with LLMs using a terminal-based interface that connects to Notion.
Enables efficient read-only access to Notion content for AI assistants by reducing the number of exposed API tools.
Orchestrates interactions with Amazon Bedrock for model control plane (MCP) functionalities.
Facilitates asynchronous video generation using Amazon Nova Reel and AWS Bedrock through a Model Context Protocol (MCP) server.
Streamlines resume creation and analysis by integrating with the NovaCV API for PDF generation, format conversion, and content analysis.
Enables searching the National Provider Identifier (NPI) registry via a Model Context Protocol (MCP) server for integration into LLM contexts.
Manages NPM packages and dependencies through interaction with LLMs, enabling package search and updates.
Provides up-to-date documentation for npm packages directly in your IDE by fetching the latest README from either GitHub or the bundled package.
Analyzes NPM packages using AI to provide real-time insights into security, dependencies, and performance.
Retrieves data from the National Park Service API, allowing users to fetch park lists and detailed information.
Query APIs for national park overviews, trails, alerts, events, and weather forecasts, making park data accessible to LLMs.
Provides real-time Dutch Railways (NS) data for comprehensive journey planning, live departures, disruption alerts, and station search.
Enables AI assistants to interact with the Neuro-Symbolic Autonomy Framework (NSAF) for agent self-design.
Provides a unified interface for managing dictionary data, articles, and user contributions for NTeALan REST APIs, designed for easy integration and extension.
Enrich banking data using the Ntropy API for use in LLM agents.
Executes Nushell scripts via the Model Context Protocol.
Manages and summarizes textual notes using the Model Context Protocol.
Orchestrates automated vulnerability scanning and template generation using an AI-augmented platform built around Nuclei.
Enables programmatic control and UI automation of macOS applications through accessibility APIs for AI agents and Swift applications.
Provides accurate interface and enum definitions directly from NuGet packages to reduce LLM hallucinations about real package APIs.
Performs tasks within the Nuke compositing software.
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.