LLM Access
Provides access to various Large Language Models (LLMs) through an MCP server.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Provides access to various Large Language Models (LLMs) through an MCP server.
Detects and lists Model Context Protocol (MCP) configurations in the local development environment.
Empowers Claude to interact with websites using LSD SQL for advanced data extraction and manipulation.
Implements the Model Context Protocol (MCP) over Server-Sent Events (SSE) in Elixir.
Exposes the Mythic framework as an MCP server for Large Language Model (LLM) integration.
Enables interaction with NetBox data via Large Language Models (LLMs) using the Model Context Protocol (MCP).
Enables AI assistants to perform advanced PDF processing operations by integrating with the Nutrient Document Web Service (DWS) Processor API.
Provides specialized AI agents for investment research of public and private markets, accessible through a simple prompt interface.
Enables AI assistants to securely interact with Odoo ERP systems through standardized data retrieval and manipulation.
Provides AI models with rich UI context and powerful interaction capabilities using Microsoft OmniParser and Model Context Protocol (MCP).
Centralizes feature requests, bug reports, and improvement suggestions for the OneMCP platform.
Enables AI assistants to access and utilize OpenAI's web search functionality during conversations.
Enables AI assistants to access and scrape web data using Oxylabs' web scraping technology.
Enables LLMs to manipulate PDF files through merging, extracting pages, and searching content.
Enables programmatic interaction with Pulumi CLI and Cloud API through the Model Context Protocol.
Loads and serves multiple OpenAPI specifications, enabling LLM-powered IDE integrations for API development.
Enables AI assistants to interact with a Roam Research graph through a standardized Model Context Protocol (MCP) interface.
Provides a type-safe Rust implementation of the Model Context Protocol (MCP) schema, ensuring alignment with the latest specifications.
Enables retrieval of PDF documents and metadata from AWS S3 buckets for use in Large Language Model contexts.
Automates interactions with SAP GUI using simulated mouse clicks and keyboard input for programmatic control.
Integrates with the Box API to perform operations such as file search, text extraction, and AI-based querying.
Empowers AI agents to efficiently navigate and search codebases semantically, significantly reducing token consumption.
Dynamically configure Model Context Protocol (MCP) server arguments at runtime.
Dynamically defines mcp tools at runtime by scraping Swagger UI and extracting the swagger.json file.
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.