This server is a discovery and recommendation tool for finding external Model Context Protocol (MCP) servers based on natural language queries.
- Find MCP Servers: Searches and recommends existing MCP servers from the internet based on specific needs.
- Detailed Results: Returns information including server IDs, descriptions, GitHub URLs, and similarity scores.
- Specific Queries: Works best with specific and actionable requests to ensure accurate recommendations.
- Real-time Information: Provides up-to-date recommendations from currently available MCP servers.
The README includes a demo image showing Airtable Server Search as an example of MCP Compass capabilities, suggesting it can help discover and connect to Airtable MCP services.
MCP Compass 🧭
MCP Discovery & Recommendation
Experience MCP Compass 🌐
You can now experience MCP discovery directly on our website!
👉 Explore MCP Compass 👈
Dive in to discover the power of MCP services in action with real-time recommendations and insights.
What is this? 🤔
MCP Compass is a discovery & recommendation service that helps you explore Model Context Protocol servers. It acts as a smart guide that helps AI assistants find and understand available MCP services out there based on natural language queries, making it easier to discover and utilize the right tools for specific tasks.
Quick Example
Features 🌟
- 🔍 Smart Search: Find MCP services using natural language queries
- 📚 Rich Metadata: Get detailed information about each service
- 🔄 Real-time Updates: Always up-to-date with the latest MCP services
- 🤝 Easy Integration: Simple to integrate with any MCP-compatible AI assistant
Quick Start 🚀
Usage
- Clone the repository
or
- Use
npx
Installation
For Claude Desktop, edit your claude_desktop_config.json
file:
MacOS/Linux
Windows
- As an MCP Service:Add to your AI assistant's MCP configuration to enable service discovery capabilities.or
License 📝
MIT License - See LICENSE file for details.
Support 💬
MCP Compass is a discovery and recommendation service that assists AI assistants in finding and understanding Model Context Protocol servers through natural language queries.
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