Prem
Implements an MCP server for Prem AI, enabling integration with Claude and other MCP-compatible clients.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Implements an MCP server for Prem AI, enabling integration with Claude and other MCP-compatible clients.
Enables AI models to programmatically search the PRIDE Archive for proteomics datasets using structured function calling.
Provides a custom server with tools for generating prompts, issuing commands, listing repositories, and running tests.
Provides search access to Prisma Cloud documentation and API references for MCP-compatible clients.
Searches private GitHub repositories, providing access to files, commit history, and issue tracking.
Provides a Model Context Protocol (MCP) server implementation, enabling privateGPT as an agent for seamless integration with any MCP-compatible application.
Categorizes and provides tools for a variety of software development and management purposes.
Enables Large Language Models to interact with the Procore construction management platform.
Enhances code development with component and page-level prompts, and basic vision integration.
Integrates the Productboard API into agentic workflows.
Provides an extensible and production-ready template for building async Model Context Protocol (MCP) servers in Python.
Serves as a backend for managing product-related data.
Analyzes project structures and generates comprehensive README files.
Analyzes project structures and manages files with advanced search and dependency management capabilities.
Manages software projects with integrated tracking, note-taking, and GitHub synchronization.
Showcases Agent Communication Protocol (ACP), Agent-to-Agent (A2A), and Model Context Protocol (MCP) capabilities through a collaborative research swarm.
Manages projects and tasks through a TypeScript-based REST API with .
Executes npm and npx commands via a server, designed for use with LLMs.
Manages and serves AI prompts with versioning and seamless integration for development environments like Cursor.
Connects to the Prometeo API to access banking information, validate accounts, and query CURP data.
Cleans and normalizes large language model prompts, redacts sensitive information, and standardizes output formats.
Transform simple questions into comprehensive, context-aware prompts by leveraging advanced prompt engineering techniques and local code context.
Automates UI testing for mobile applications using LLMs and Appium.
Manages and serves customizable prompt templates for use by MCP 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.