Coder
Empowers AI assistants with persistent memory, deep code understanding, and context-aware development capabilities for software projects.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Empowers AI assistants with persistent memory, deep code understanding, and context-aware development capabilities for software projects.
Connects AI development tools to CodeRide, an AI-native task management system, enabling project understanding, task automation, and collaboration.
Exposes the codetoprompt library through the Model Context Protocol (MCP), enabling LLM agents to programmatically generate prompts and analyze code.
Automates repetitive coding tasks and provides AI assistance to streamline software development workflows.
Demonstrates how Claude AI can be integrated into Java EE development workflows using the Model Context Protocol (MCP).
Enables AI assistants to securely manage and interact with cryptocurrency nodes via RPC interfaces.
Integrates ComfyUI workflows into Open WebUI pipelines for image generation.
Enables unstructured document processing for AI chatbots by extracting data from PDF files.
Enables AI tools to interact with Keyfactor Command for certificate management functions.
Provides a secure, containerized interface for remote command execution.
Supports compliance operations in AI agents by providing CLI tools and an MCP server for interacting with compliance data.
Enables AI agents to interact with the Concordium blockchain through natural language queries.
Manages multiple parallel browser instances for concurrent web automation tasks using Playwright.
Enables AI assistants to solicit user confirmation and clarification through a standardized Model Context Protocol (MCP) elicitation process.
Enables AI-powered interaction with Confluence Cloud through a Spring Boot-based Model Context Protocol server.
Enables users to play Connect 4 against an AI assistant through an MCP server.
Automates and monitors console applications, enabling AI assistants to fully interact with terminal workflows, similar to Playwright for web browsers.
Solve complex combinatorial and numerical optimization problems with a unified interface to multiple powerful solvers, empowering AI assistants.
Provides a robust interface to manage Docker and Podman containers, networks, volumes, and Docker Swarm services.
Automates deployments to the Container Inc. platform.
Integrates a continuous, background cognitive processing system that enables AI models to think between conversations.
Integrates AI-powered productivity applications for task management, idea development, journal analysis, and time tracking with large language models via the Model Context Protoco…
Performs comprehensive project analysis through real code parsing, AST-level component extraction, and intelligent context generation for AI coding assistants.
Enables AI models, such as LM Studio, to securely interact with local data and custom tools by implementing the Model Context Protocol.
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.