MCP Development with Amazon Lambda and Gemini CLI

Leveraging Gemini CLI and the underlying Gemini LLM to build Model Context Protocol (MCP) AI applications with Python from a local development environment deployed to the Lambda service on AWS. Aren’t There a Billion Python MCP Demos? Yes there are. Python has traditionally been the main coding language for ML and AI tools. The goal of this article is to provide a minimal viable basic working MCP stdio server that can be run locally without any unneeded extra code or extensions. What Is Python? Python is an interpreted language that allows for rapid development and testing and has deep libraries for working with ML and AI: Welcome to Python.org Python Version Management One of the downsides of the wide deployment of Python has been managing the language versions across platforms and maintaining a supported version. The pyenv tool enables deploying consistent versions of Python: GitHub - pyenv/pyenv: Simple Python version management As of writing — the mainstream python version is 3.13.