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Guide: Deploy Google Gemma 4 on Amazon SageMaker with vLLM and MCP Tools

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A developer has published a step-by-step guide for deploying Google's Gemma 4 E2B model to an Amazon SageMaker real-time endpoint running on a single NVIDIA L4 GPU. The setup uses AWS's published vLLM container for SageMaker and relies entirely on plain AWS CLI commands, making each step executable manually or via an MCP server. A Python-based MCP server built on the MCP SDK 2.x exposes annotated tools for managing the deployment, from endpoint creation to deletion, with Claude Code acting as the MCP client. SageMaker handles infrastructure concerns such as container health checks, request routing, and CloudWatch logging, eliminating the need to manage instances or load balancers directly. The project code is publicly available on GitHub and requires Python 3.11 or newer, AWS CLI v2, and a SageMaker quota for a compatible ml.g6 instance type.

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