Gemma 4 on an Amazon SageMaker Endpoint: AWS CLI, NVIDIA L4, and an MCP Server
This article provides a step by step deployment guide for Gemma 4 E2B to an Amazon SageMaker 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/sagemaker-gemma What is this project trying to Do? This project serves Gemma 4 E2B from a SageMaker real-time endpoint on one NVIDIA L4 GPU,…
This article provides a step-by-step deployment guide for Gemma 4 E2B to an Amazon SageMaker hosted GPU enabled system. The project aims to serve Gemma 4 E2B from a SageMaker real-time endpoint on one NVIDIA L4 GPU using the vLLM container AWS publishes for SageMaker. The article outlines the eight-step deployment process, including setting up the basic environment, installing the required Python packages, configuring the environment variables, and deploying the model using AWS CLI commands.
The project also includes a simple MCP (Model Management Control Plane) transport using stdio, where the client launches the server as a local process and communicates with it over stdin and stdout.
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