MCPHubs - Model Context Protocol Projects Hub

What is MCPHubs - Model Context Protocol Projects Hub?

MCPHubs is a website built with Next.js that showcases projects related to Anthropic's Model Context Protocol (MCP). It retrieves MCP-related projects from GitHub and uses Google Cloud Vertex AI (Gemini Pro) to analyze their content and assess relevance to the MCP ecosystem.

How to use MCPHubs - Model Context Protocol Projects Hub?

Clone the repository, run npm install, configure a .env.local file with your GITHUB_TOKEN and Google Cloud Vertex AI credentials, then start the development server with ./start-dev.sh. The site runs on http://localhost:3001 by default and can be deployed to Vercel or Netlify.

Key features of MCPHubs - Model Context Protocol Projects Hub

• GitHub API integration to retrieve MCP-related projects
• AI analysis using Google Gemini Pro for relevance scoring
• Project list and detailed project pages with README content
• Environment-aware proxy for CORS in development
• Responsive design for various device sizes

Use cases of MCPHubs - Model Context Protocol Projects Hub

• Discover and browse open-source projects that implement or relate to MCP
• Evaluate project relevance to MCP using AI-powered analysis
• View detailed project information, including stars, description, and README
• Quickly find MCP-compatible tools and integrations

FAQ from MCPHubs - Model Context Protocol Projects Hub

What data does MCPHubs use and where does it come from?

MCPHubs retrieves project data from the GitHub API and analyzes it using Google Cloud Vertex AI (Gemini Pro). All analysis is performed server-side.

What are the requirements to run MCPHubs locally or deploy it?

You need a GitHub API token (optional but recommended), a Google Cloud project with Vertex AI enabled, and a service account credentials file with Vertex AI user permissions.

Does MCPHubs support production deployment?

Yes, it can be deployed to Vercel, Netlify, or any platform supporting Next.js. The proxy is automatically disabled in production, and environment variables must be set accordingly.

How is authentication and proxy configured?

In development, the app auto-enables proxies for GitHub and Vertex AI APIs to avoid CORS issues. In production, proxies are disabled and APIs are called directly.

What is the AI analysis based on?

The AI uses Google Gemini Pro to evaluate project content and assign a relevance score to the MCP ecosystem, displayed on each project's detail page.