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

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A developer has published a step-by-step guide for deploying Google's Gemma 4 E2B language model to an Amazon SageMaker real-time endpoint running on a single NVIDIA L4 GPU. The setup uses AWS's published vLLM container and relies entirely on standard AWS CLI commands, making each step reproducible manually or through an MCP server. A Python-based MCP server built on the MCP SDK 2.x provides tools for managing the deployment, with Claude Code acting as the MCP client via stdio transport. SageMaker handles infrastructure concerns such as container placement, health checks, request routing, and logging to CloudWatch, eliminating the need to manage instances or load balancers. The project is open source and available on GitHub, requiring Python 3.11 or newer, AWS CLI v2, and a SageMaker endpoint quota for a compatible L4 GPU instance type.

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