2B Gemma 4 Deployment with Cloud Run, NVIDIA L4, MCP SDK 2.x, and Claude Code
This article provides a step by step deployment guide for Gemma 4 E2B to a Cloud Run hosted GPU enabled system. A suite of Python MCP tools is built to simplify management of the vLLM hosted deployment with Claude Code. https://github.com/xbill9/gemma4-dev/tree/main/gpu-2B-cloudrun-devops-agent What is this project trying to Do? This project is a DevOps/SRE assistant for a Gemma 4 model served by…
This project is a DevOps/SRE assistant for deploying a Gemma 4 model using vLLM on Cloud Run with an NVIDIA L4 GPU. The deployment is managed through a single-file Python MCP server that simplifies tasks such as staging weights, deploying the service, checking health, benchmarking, and tearing down the deployment. The MCP server operates in a serverless environment where it scales to zero when idle.
The MCP server relies on the MCP Python SDK version 2.x, which has undergone a recent migration. This migration necessitated updating the import statement and constructor from FastMCP to MCPServer within the server code, as well as installing the httpx2 package instead of the now-unavailable httpx. The project also introduces an MCP server that communicates with Claude Code, a tool used for model management.
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