What models does it support?
It supports models from GitHub Models and AzureML, including OpenAI, Microsoft (e.g., Phi-3), Meta (Mistral), and others. Note that models like "Phi-4" or "Phi-3-mini-4k-instruct" may not be currently available.
@michaelwybraniec
Basic information
No overview available yet
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-server-gh-models-helper": {
"command": "npx",
"args": [
"@modelcontextprotocol/inspector",
"dist/index.js"
]
}
}
}Tool 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.
Fetch the live tool list by running this server in a temporary sandbox using the button above.
This MCP server helps you interact with and compare different language models available via GitHub Models and AzureML, including OpenAI, Microsoft, Meta, Mistral, and more. It is designed for developers who need to explore, filter, and test models programmatically.
Install dependencies (npm install), set up environment variables (copy .env.template to .env with your GitHub token), build the project (npm run build), and run in development mode using npx @modelcontextprotocol/inspector dist/index.js. Add the server to Claude Desktop by editing claude_desktop_config.json with the node command, path to dist/index.js, and the GITHUB_TOKEN environment variable.
It supports models from GitHub Models and AzureML, including OpenAI, Microsoft (e.g., Phi-3), Meta (Mistral), and others. Note that models like "Phi-4" or "Phi-3-mini-4k-instruct" may not be currently available.
Node.js and npm are required. The server runs locally as a JavaScript process and uses the Model Context Protocol (MCP) to communicate with AI clients.
You must provide a GitHub Personal Access Token in the `GITHUB_TOKEN` environment variable. No other authentication is needed.
All model metadata and responses are fetched live from GitHub Models and AzureML APIs. No local caching or storage of responses is described.
The README explicitly shows integration with Claude Desktop, but as an MCP server it should be compatible with any MCP‑aware client.
This MCP server provides integration with Gerrit code review system, allowing AI assistants to review code changes and their details through a simple interface.

Model Context Protocol Servers
Interact seamlessly with GitLab repositories to manage merge requests and issues. Fetch details, add comments, and streamline your code review process with ease.
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Model Context Protocol Servers
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