Core Lightning
Provides a standardized gRPC interface for Core Lightning nodes, enabling control via Large Language Models (LLMs) using the Model Context Protocol (MCP) specification.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Provides a standardized gRPC interface for Core Lightning nodes, enabling control via Large Language Models (LLMs) using the Model Context Protocol (MCP) specification.
Provides a lightweight C++ coroutine library built on C++20, offering a foundational framework for Model Context Protocol (MCP) servers.
Integrates the Coroot observability platform, enabling AI agents and MCP clients to access monitoring, troubleshooting, and configuration capabilities.
Provides a Model Context Protocol (MCP) server that grants access to the Cortex API, leveraging relevant workspace context to answer natural language queries about your system's s…
Connects MCP clients to Cortex, enabling threat intelligence analysis via tools consumable by large language models.
Enables AI models to search and retrieve information from Cortex Cloud documentation and API references.
Provides an interface for interacting with Cosense pages through a standardized protocol.
Enables Large Language Models to directly query and interact with Azure Cosmos DB data.
Enables querying Cosmos DB data from Claude Desktop using CData JDBC drivers.
Enables interaction with Azure Cosmos DB through a Model Context Protocol (MCP) server built with the Go SDK.
Fetches real-time COVID-19 statistics for any country.
Establishes a Model Context Protocol (MCP) server for seamless integration with various development clients.
Enables AI agents to interact with your API.
Enables AI assistants to programmatically manage cPanel email accounts, passwords, quotas, and forwarders via API.
Provides a robust, high-performance C++ implementation of the Model Context Protocol (MCP) server utilizing StreamableHTTP transport.
Expose public Rust APIs to language models using `cargo public-api`.
Provides a modular web crawler and a REST API for managing and storing webpage data, integrated with an MCP server.
Scaffold Model Context Protocol (MCP) server applications rapidly with TypeScript and modern development tooling.
Scaffolds a Model Context Protocol (MCP) server with integrated web capabilities.
Scaffolds standardized Model Context Protocol (MCP) servers using Node.js.
Bridges AI agents with enterprise systems using the Model Context Protocol (MCP) and provides an API for ComfyUI-node compatible LLM and agent use.
Enables AI interactions with the Cribl API by providing a Model Context Protocol (MCP) server.
Fetches comprehensive cricket data from Cricbuzz, including player statistics, live match scores, upcoming schedules, and the latest news.
Manages Croit Ceph clusters by dynamically generating tools from their OpenAPI specifications, optimizing for AI interaction.
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.