Grasshopper
Bridges Grasshopper and Claude Desktop for natural language control of parametric design.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Bridges Grasshopper and Claude Desktop for natural language control of parametric design.
Provides HR-related tools, satirically designed for a corporate dystopia, accessible through a Model Context Protocol (MCP) server.
Analyzes Instagram engagement metrics to generate leads, extract demographic insights, and analyze audience feedback.
Enables natural language management of Active Directory users, groups, and computer objects.
Creates multiple implementations of proposed software features using coding agents and a unified API for tool access.
Monitors and analyzes potential security risks during the loading and execution of machine learning and artificial intelligence model files.
Downloads webpages as Markdown files for easy access and integration with AI tools.
Provides mathematical and statistical functions to Large Language Models (LLMs) via a simple API.
Provides a production-ready template for building Model Context Protocol (MCP) servers with TypeScript.
Generates memes from user prompts using the ImgFlip API.
Aggregates trending news and hot topics from multiple platforms via the Newsnow API, leveraging the Model Context Protocol (MCP).
Enables Large Language Models to interact with and automate tasks within a Nextcloud instance.
Connects to Nomad to provide a Model Context Protocol (MCP) server.
Enables AI models to interact with the Nostr decentralized social network.
Automates server, network device inspection, and IT operations with AI-driven monitoring and anomaly detection.
Exports 1C:Enterprise platform context from help files into multiple formats for LLMs and offers an MCP server for AI assistant integration.
Enhance and standardize prompts for Large Language Models (LLMs) through composable decorators with this framework.
Enables Model Context Protocol (MCP) clients to interact with RabbitMQ queues and topics.
Deploys a complete AWS backend infrastructure for retrieval-augmented generation applications, integrating with Gemini Pro and a Streamlit UI.
Provides ripgrep search capabilities to Model Context Protocol (MCP) clients.
Enables building Model Context Protocol (MCP) clients and servers in Go.
Streamline code snippet organization and clipboard management for developers with tag-based search and AI-assistant integration.
Provides comprehensive access to academic paper data, author information, and citation networks via the Semantic Scholar API.
Enables Claude to execute shell commands securely through 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.