MCP Compass MCP Server

What does “MCP Compass” MCP Server do?

MCP Compass is a discovery and recommendation service designed for the Model Context Protocol (MCP) ecosystem. It acts as a smart guide to help AI assistants and developers find and understand available MCP servers using natural language queries. By providing detailed metadata, real-time updates, and easy integration, MCP Compass simplifies the process of discovering the right MCP tools for any specific task. This enables AI systems to seamlessly access external data sources, APIs, and services, thereby enhancing development workflows with up-to-date and relevant capabilities. MCP Compass is especially useful for surfacing MCP services dynamically, ensuring that AI agents are always aware of the latest tools and functionalities available in the MCP landscape.

List of Prompts

No prompt templates were found in the repository or documentation.

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List of Resources

No specific MCP resources are detailed in the repository or documentation.

List of Tools

No tool definitions or server.py implementation were found in the repository or documentation.

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Use Cases of this MCP Server

• MCP Service Discovery
  Easily find MCP servers relevant to your workflow or user needs through natural language queries, helping developers and AI assistants quickly locate the right tools.
• Real-Time Recommendation
  Get up-to-date suggestions for new or trending MCP services, ensuring that teams stay current with the evolving MCP ecosystem.
• Metadata Enrichment
  Access detailed information about MCP servers, enabling informed decisions when selecting services or integrating with new tools.
• Easy Integration in AI Assistants
  Seamlessly plug MCP Compass into any MCP-compatible AI assistant to enable dynamic tooling and service selection.
• Centralized MCP Search
  Use MCP Compass as a unified entry point to explore the MCP landscape, removing the need to manually search or track servers across disparate sources.

How to set it up

Windsurf

No specific setup instructions for Windsurf are provided.

Claude

1. Locate your claude_desktop_config.json file:
   • macOS/Linux:
     ~/Library/Application Support/Claude/claude_desktop_config.json
   • Windows:
     $env:AppData\Claude\claude_desktop_config.json
2. Open the configuration file in your code editor.
3. Add the MCP Compass server entry:

   {
     "mcpServers": {
       "mcp-compass": {
         "command": "npx",
         "args": [
           "-y",
           "@liuyoshio/mcp-compass"
         ]
       }
     }
   }
   

4. Save the file and restart Claude Desktop.
5. Verify that MCP Compass appears as an available MCP server.

Securing API Keys

No API keys are required or mentioned for MCP Compass.

Cursor

No specific setup instructions for Cursor are provided.

Cline

No specific setup instructions for Cline are provided.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "mcp-compass": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “mcp-compass” to the actual name of your MCP server and replace the URL with your own MCP server URL.

Overview

Based on the available documentation, MCP Compass is a promising discovery tool, but the lack of documented prompts, resources, and tool definitions limits its current utility for direct LLM workflow integration. It is, however, valuable for MCP exploration and recommendation.

MCP Score