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MCP Server Directory
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
MCP Servers listings
CL
Clipboard
CommunityProvides MacOS clipboard access for AI assistants via the Model Context Protocol.
CL
Clockify
CommunityManages time entries in Clockify using AI tools and natural language prompts.
CC
Cloudeka Cldkctl
CommunityProvides access to Cloudeka's cldkctl CLI functionalities as Model Context Protocol (MCP) tools for AI clients like Claude Desktop and Cursor.
CA
Cloudinary Analysis JS
CommunityAnalyze external assets to extract detailed information based on various AI-driven analysis types.
CO
Coco
CommunityFacilitates pair programming by providing code review with contextual questioning, prompting developers to refine their solutions.
CA
Code Agent
CommunityImplements an AI agent that interacts with the MCP framework using OpenAI LLMs to perform code actions.
CE
Code Expert System
CommunitySimulate code reviews from expert personas using AI and a knowledge graph.
CE
Code Explainer
CommunityAnalyzes and explains code with a comprehensive breakdown of structure and functionality.
CL
Code Line Counter
CommunityTrack and analyze the scale of AI-generated code by counting lines of code, comments, and blank lines across various programming languages.
CR
Code Reference Optimizer
CommunityOptimizes code context extraction, diff analysis, and import management to minimize token usage for AI assistants.
Automates GitHub Pull Request reviews by integrating local development toolchains and AI.
CR
Code Review Assistant
CommunityAutomates preliminary code feedback, including syntax checking, code explanation, and improvement suggestions, via a multi-agent system.
CR
Code Reviewer
CommunityProvides AI-powered code reviews using OpenRouter's LLM models via the Model Context Protocol.
CO
CodeAnalysis
CommunityAnalyzes codebases to provide AI-assisted code understanding and transformation capabilities.
CC
Codebase Curator
CommunityEmpowers AI assistants to deeply understand and effectively work with any codebase through AI-powered analysis.
CO
Codebox
CommunityProvides a remote coding environment for AI agents to autonomously develop applications and scripts.
CO
CodeChecker
CommunityAnalyzes code and provides intelligent suggestions using OpenAI's GPT models within the Cursor IDE.
CO
CodeCompass
CommunityEnables intelligent repository analysis and AI-powered development assistance via an enterprise-grade Model Context Protocol (MCP) server.
CO
CodeMasterPro
CommunityRefines code using AI powered by Gemini and Brave.
CN
CodeQL N1ght
CommunityProvides a standardized interface for AI assistants to interact with the CodeQL N1ght tool for automated code analysis.
CO
Coder
CommunityEmpowers AI assistants with persistent memory, deep code understanding, and context-aware development capabilities for software projects.
CO
CodeRide
CommunityConnects AI development tools to CodeRide, an AI-native task management system, enabling project understanding, task automation, and collaboration.
CO
CodeToPrompt
CommunityExposes the codetoprompt library through the Model Context Protocol (MCP), enabling LLM agents to programmatically generate prompts and analyze code.
What Are MCP Servers?
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 →
How MCP Servers Work
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.
Types of MCP Servers
- Code Completion Servers: Enhance AI coding assistants with context from your codebase, documentation, and project structure.
- API Integration Servers: Connect AI to REST APIs, GraphQL endpoints, and web services for real-time data access.
- File Management Servers: Enable AI to read, write, and organize files in your development environment.
- Data Analysis Servers: Connect AI to databases, data warehouses, and analytics tools.
Choosing the Right MCP Server
When selecting an MCP server, consider:
- IDE Compatibility: Ensure it works with Cursor, VS Code, or your preferred editor
- Use Case Match: Choose servers designed for your specific needs
- Maintenance Status: Prefer actively maintained servers with recent updates
- GitHub Activity: Higher stars and recent commits indicate quality
Popular Use Cases
- AI-Powered Code Completion Enhance Cursor and Claude with project-specific context.
- Automated API Testing Connect AI to your APIs for intelligent testing and debugging.
- Database Querying Let AI write and execute SQL queries against your databases.
For detailed setup guides, see our Complete MCP Server Setup Guide →
Frequently Asked Questions About MCP Servers
Everything you need to know about installing, using, and troubleshooting Model Context Protocol.
How do I install MCP servers in Cursor?
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.
What's the difference between MCP servers and VS Code extensions?
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.
Are these MCP servers free to use?
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.
Can I build my own MCP server?
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.
What is a Model Context Protocol (MCP) server?
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.
How do MCP servers work with Claude?
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.
What are the best MCP servers to start with?
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.
How do I install and configure MCP servers?
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.
Are MCP servers secure?
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.
What's the difference between MCP resources, tools, and prompts?
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.
Which AI clients support MCP besides Claude Desktop?
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.
How often is this MCP servers directory updated?
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.
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