fleet — let your coding agent use every machine you have

Claude Code, Codex and Gemini see one machine: the one they run on.
fleet shows them all of yours — every GPU, how much is free, and how to get there.

The problem

Ask your agent to train a model and it starts on your laptop — while a 4090 sits idle across the room and a rented A100 bills you by the hour. It cannot use what it cannot see.

• Your agent is stuck on one machine. It has no idea your other boxes exist.
• Finding a free GPU is manual. SSH into five hosts, run nvidia-smi, compare in your head.
• Handing it a server means pasting credentials into the chat, and hoping.

Get started: ask your agent

Install it on the machine that will be your fleet's center — the one that keeps the list of your machines and decides which may reach which — so pick one that can reach all your devices and is online most of the time, such as a desktop or home server (you can move the role later). There, paste this into Claude Code, Codex, Gemini CLI, or any agent that can run commands:

Install fleet from https://github.com/lion-zhang/fleet

_{Agents: the steps are in INSTALL.md.}

That is the whole setup. fleet is installed once on this machine, and every supported agent you have here learns it — not only the one you asked. From here on you say what you want in plain words, with no commands to remember.

Then add your machines

Tell the agent how you reach a machine — the SSH command you already use is enough:

You: add my GPU server, ssh ubuntu@10.0.0.7

Agent: Added as gpu-box: 2× RTX 4090, both idle, 46 GB free. It's ready to use.

Each one takes a sentence, whatever the machine is:

Nothing is installed on the machines you add: they only need SSH, on Linux, macOS or Windows. fleet probes each one for its GPUs, memory and disks, and keeps that current.

Then let the agent pick

You describe the work; the agent finds where it fits. It checks what each machine has and what is free on it right now, so it will not send a job to a busy card:

You: train train.py on whatever has a free 24 GB card

Agent: rtx4090 has 23.1 GB free and an idle GPU; a100-spot is free too but costs $1.89/hr. Starting on rtx4090, logging to train.log.

Keys and passwords never go into the conversation, and anything irreversible waits for your yes.

Only install fleet where you use it. The machines you add above need nothing but SSH: fleet measures them and connects to them from the center. Install fleet on another machine only if you also run agents there, or want to check the fleet from it. That machine becomes a member: ask the center's agent to "invite" it, and paste the line it gives you into a terminal there, or give it to the agent there.

An app that cannot run commands?

Desktop apps and editors get fleet in one click; it runs as an MCP server:

App	Install
Claude Desktop	open fleet.mcpb from the latest release
Cursor
VS Code

Plus plugins for Claude Code, Codex, Copilot CLI and Gemini CLI, and OpenCode, Amp, Windsurf, Cline, Zed, Qwen Code, Goose, Kiro, Hermes — 35+ agents in all: every agent →

Built to be safe

• Nothing to install on your machines. fleet probes with one script over one SSH connection — Linux, macOS or Windows. A NAS or a fresh rental works as it is.
• Keys, not passwords. A password, if needed at all, is typed once by you. Nothing that could be stolen is stored, and the agent never sees a credential.
• Access you control. The center decides which machine may reach which, and a revoke is pushed at once. fleet access gpu-box --allow laptop, --deny to take it back.
• The agent asks, not guesses. It is told to ask which machine you mean, and to leave irreversible commands to you.

Prefer the command line?

Everything the agent does is a plain fleet command. To install fleet yourself, run this on the machine you work from (this is also what your agent runs when you ask it):

curl -LsSf https://raw.githubusercontent.com/lion-zhang/fleet/main/install.sh | sh

_{Windows: powershell -ExecutionPolicy ByPass -c "irm https://raw.githubusercontent.com/lion-zhang/fleet/main/install.ps1 | iex"}

Then drive it yourself:

fleet ls                            # every machine, with what is free right now
fleet ls --tag cuda --tag vram-24g  # by capability: NVIDIA, a card of 24 GB or more
fleet top                           # live view, like htop for the whole fleet
fleet show gpu-box                  # one machine in detail: GPU processes, services, disks
fleet ssh gpu-box -- nvidia-smi     # run something there
fleet add "ssh ubuntu@10.0.0.7"     # add a machine; fleet invite NAME for a join line
fleet access nas --allow laptop     # let one machine reach another

Rentals from vast.ai, RunPod or AutoDL show their price (fleet edit a100 --cost 1.89), the fleet's burn rate, and an alert when a rental sits idle. On Tailscale, ZeroTier or WireGuard? fleet just needs an address it can route to.

How fleet compares

fleet is about the machines you already have. It complements tools that launch new ones.

FAQ

Setting up

Safety

Machines

Learn more

• Getting started — your first fleet, in ten minutes
• Guides — adding machines, finding the right one, access, the center, Windows
• Every agent — install commands and config for 35+ agents
• Command reference — every command and option
• How fleet works — what happens, step by step, under the hood
• Design — one core per machine, a skill per agent, MCP for the rest; access and sync
• All documentation

Status: v0.5. The test suite runs on Linux, macOS and Windows, and every command is run end to end on a real machine of each OS in CI — from a script, as an agent runs it, and at a real terminal, as you do. Multi-machine fleets (key, password, invite, handover) are tested on Linux machines built from scratch.

Issues and pull requests are welcome — see CONTRIBUTING.md. If fleet saved you a GPU-hour, a ⭐ helps other people find it.

MIT