kubectl-ai is a Go CLI and kubectl plugin that sends a prompt to an LLM, which proposes and runs kubectl and bash commands against your cluster. It supports Gemini (default), Vertex AI, OpenAI, Azure OpenAI, Grok, Bedrock, Ollama and llama.cpp. It can also act as an MCP server or client, and offers a terminal or web UI.
Who it is for: Kubernetes operators who want an LLM agent in the terminal
Strengths
Works with many providers, including local Ollama and llama.cpp models
Runs interactively, one-shot, or from stdin pipes, and as a `kubectl ai` plugin
Acts as MCP server and client; custom tools are defined in YAML
Opt-in session save and resume across runs
Weaknesses
Not an officially supported Google product
MCP streamable-http endpoint is unauthenticated unless OAuth 2.1 flags are set
Local models need --enable-tool-use-shim for tool calling
Runs kubectl and bash, so cluster changes depend on LLM output and permission prompts
What it needs
no GPU
Needs kubectl, LLM provider API key or local Ollama/llama.cpp
Models: gemini, vertexai, openai, azopenai, grok
port 8888
Quick answers
Is kubectl-ai open source?
Yes. Its code is on GitHub under the Apache-2.0 license.
Can you run kubectl-ai with Docker?
Yes. Its repository has a Docker setup: a Dockerfile, a Compose file or a published image.
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