AlexBodner/gcloud-gpu-agent

gcloud-gpu-agent

🤖 An AI agent skill that spins up and drives Google Cloud GPUs for you.

Ask your agent to "launch an L4 and run my training" — it creates the VM, pushes your repo, kicks off the job in a detached session, streams the logs, pulls your results, and reminds you to shut it down. Works with Claude Code and Codex CLI. Powered by one dependency-free Bash script wrapping gcloud, so it also works as a plain CLI.

Claude Code:

/plugin marketplace add AlexBodner/gcloud-gpu-agent
/plugin install gcloud-gpu-agent@alexbodner-gcloud-gpu-agent

Codex CLI:

# 1. Install the CLI (needed so the agent can call gpu-vm commands)
curl -fsSL https://raw.githubusercontent.com/AlexBodner/gcloud-gpu-agent/main/install.sh | bash

# 2. Add the skill to your project (or ~/.codex/skills/ for global use)
mkdir -p .codex/skills/gcloud-gpu-agent
curl -fsSL https://raw.githubusercontent.com/AlexBodner/gcloud-gpu-agent/main/.codex/skills/gcloud-gpu-agent/SKILL.md \
  -o .codex/skills/gcloud-gpu-agent/SKILL.md

Now just talk to your agent:

"Spin up an A100, push this repo, and start train.py in tmux." "Tail the training log." · "Pull the checkpoints and stop the VM."

The agent runs the right commands under the hood and reads the output back for you.

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Use it as a plain CLI too

The same tool works without an agent:

curl -fsSL https://raw.githubusercontent.com/AlexBodner/gcloud-gpu-agent/main/install.sh | bash

GPU=nvidia-l4 gpu-vm create                         # 🚀 a 24GB GPU box, ~90 seconds
gpu-vm push ~/my-project                            # 📦 upload (private repos OK)
gpu-vm run "cd my-project && python train.py" train # 🏃 detached job in tmux
gpu-vm logs train.log                               # 📜 stream the logs
gpu-vm pull my-project/outputs ./outputs            # ⬇️  bring results home
gpu-vm stop                                         # ⏸  stop billing (disk kept)

The i