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.
@GiantClam
Basic information
MCPHubs is a website that showcases projects related to Anthropic's Model Context Protocol (MCP)
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
RepositoryTool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
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.
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.
MCPHubs retrieves project data from the GitHub API and analyzes it using Google Cloud Vertex AI (Gemini Pro). All analysis is performed server-side.
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.
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.
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.
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.
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