kube-mcp

Get a Gemini APi Key

Goto https://aistudio.google.com/ and get yourself an API Key. Currently, gemini-2.0-pro-exp-02-05 LLM is available absolutely free of charge. Other models available for very cheap price also.

Install Codename Goose

Goose is an open source AI agent that supercharges your software development by automating coding tasks. We will use Codename Goose as it has a built in MCP client. Install Codename Goose by following the steps here https://block.github.io/goose/docs/getting-started/installation. Setup GOOGLE_API_KEY environment variable so that Goose knows to use Gemini API. Understand how to configure using goose configure and start as session using goose session.

Develop MCP Server

Read about MCP by reading the documentation : https://modelcontextprotocol.io/introduction and specifically the Python SDK : https://github.com/modelcontextprotocol/python-sdk Clone this repository and test it using mcp dev server.py. Note that this project uses uv package manager instead of pip. Learn about uv by reading docs : https://github.com/astral-sh/uv This project uses the kubernetes python client: https://github.com/kubernetes-client/python

Install Minikube

Install minikube by following isntructions : https://minikube.sigs.k8s.io/docs/start/?arch=%2Flinux%2Fx86-64%2Fstable%2Fbinary+download Ensure that the config to the cluster is provided to the MCP server. Look at the KubernetesManager and config.load_kube_config() to understand how the config is loaded.

Connect your MCP server to Codename Goose

Add the MCP Server as an extension by reading the following docs : https://block.github.io/goose/docs/getting-started/using-extensions Start a new goose session using command goose session --with-builtin developer --with-extension "uvx kube-mcp"

Make it all work

Try giving a command in Goose and make it interact with Minikube using the MCP Server