Archai Static Analyzer
Analyzes code statically, potentially for security vulnerabilities or code quality issues.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Analyzes code statically, potentially for security vulnerabilities or code quality issues.
Enables AI clients to interact with Graphisoft Archicad by running a server for its Tapir add-on.
Provides an interface for interacting with the LLM CLI to get architectural design feedback.
Bridges multiple webhook endpoints into a single, unified configuration for managing and querying knowledge bases.
Automates multi-platform, one-click article publishing by integrating with MCP services.
Automates the generation, compilation, and uploading of Arduino, ESP8266, and ESP32 firmware using local Large Language Models and Arduino CLI.
Provides a server for accessing diverse information about Argentina via the Argentina Datos API.
Analyzes code repositories and performs security assessments using the Model Context Protocol (MCP).
Automates adding movies and TV shows to Radarr and Sonarr instances.
Provides tools for interacting with the Artemis API and generating formulas for crypto data analysis.
Extracts article content, including title, text, author, and date, from web URLs.
Interacts with Helm charts on Artifacthub through a Model Context Protocol (MCP) server.
Manages arXiv academic papers, offering search, PDF download links, content parsing, and access to the latest AI research.
Facilitates searching, organizing, and summarizing academic papers from arXiv.
Searches and retrieves academic papers from arXiv using the Model Context Protocol.
Enables AI assistants to search and analyze arXiv papers through a simple Message Control Protocol (MCP) interface.
Intelligently searches Software Engineering papers on arXiv, offering advanced filtering, sorting, and management capabilities.
Generates lightweight ASCII charts directly in terminal environments via a Model Context Protocol server.
Manages Model Context Protocol (MCP) servers using the asdf version manager.
Enables the construction and management of agent networks designed to interact with OpenAPI-defined APIs.
Retrieves and displays current asset price information for use by large language models.
Provides a chatbot interface that uses GPT-4o to route user input to various tools like GPT chat, image generation, Supabase queries, and text-to-speech.
Parses Go source code into an Abstract Syntax Tree (AST) and converts it into a clean, LLM-friendly format to enhance prompt context.
Parses Go source code into an Abstract Syntax Tree (AST) and converts it into a clean, LLM-friendly format for context injection.
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.