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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 and what is running on it, the models being served, the software installed, and where your models and data live.

No account, no cloud service, nothing installed on the machines you add, no keys handed out: fleet logs in exactly as you do, with the SSH you already use.

tests License: MIT Linux | macOS | Windows MCP server

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.

  • It cannot see what is running, or what is already there — whose job is on that card, which box already serves Llama 3, where the datasets live — so it downloads and installs things twice.

Related MCP server: fast-mcp-ssh

Get started: ask your agent

Paste this into Claude Code, Codex, Gemini CLI, or any agent that can run commands, on the machine you work from:

Install fleet from https://github.com/sinolion/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 — or let it look in your ~/.ssh/config and on your tailnet for machines you can already reach:

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:

The machine

What you tell the agent

a server you can already SSH into

"add ssh ubuntu@10.0.0.7" — fleet logs in as you do, with your key

one you reach with a particular key file

"add ssh -i ~/.ssh/my_key ubuntu@1.2.3.4" — or a Host from your ~/.ssh/config

a machine on your tailnet

"find my machines" — it lists your ssh config hosts and tailnet machines, and adds the ones you pick

a new rental (vast.ai, RunPod, AutoDL)

"add ssh -p 40001 root@1.2.3.4, it costs $1.89/hr" — with the key on your provider account

one that only takes a password

"add it" — fleet offers ssh-copy-id, you type the password once into ssh, and your key goes on it

one that will not let you in

"why can't you reach the NAS?" — fleet doctor names the one thing to fix

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.

You say

How the agent finds it

"what's free right now?"

every machine checked, the free ones listed

"find me a box with a 24 GB card"

matched by what machines have — NVIDIA or AMD, VRAM, cores, RAM — not by name

"run the tests on the Linux box"

the machine that runs Linux, results brought back

"what's costing me money?"

idle paid rentals flagged, with their hourly price

"who is using the GPUs?"

every job on every card — user, VRAM, how long, the command

"is Llama 3 already served somewhere?"

every model server's models, and the URL or ssh tunnel to reach it

"which box has torch 2.5 and CUDA 12?"

each machine's CUDA or ROCm, Python environments and package versions

"download the dataset where datasets go"

the folder that machine says holds datasets, and the room left there

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 need nothing but SSH. Install fleet on another machine only if you also run agents there; it works the same everywhere, with nothing to join or sync. There, fleet ls --discover lists the machines in your ssh config and on your tailnet; the ones you added by hand are in one file you can share with your dotfiles.

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

Add to Cursor

VS Code

Install in 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. The few files it does leave there are listed in What fleet changes.

  • No keys handed out, no access managed. fleet connects exactly as you do — your ssh config, your keys and agent, Tailscale SSH, your rental provider's key — and writes no keys anywhere. Who may reach what stays where you already decide it. When a machine refuses, fleet doctor tells you the fix; fleet never makes it.

  • No passwords. fleet never asks for one or stores one, and the agent never sees a credential. Secrets in a GPU job's command line are blanked before anyone sees them.

  • The agent asks, not guesses. It is told to ask which machine you mean, to leave irreversible commands to you, and not to start work on a GPU someone else is using.

  • Nothing phones home. Apart from installing and updating itself, fleet talks to your machines and nothing else: no account, no telemetry, no update check. Found a flaw? SECURITY.md says how to report it privately.

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/sinolion/fleet/main/install.sh | sh

Windows: powershell -ExecutionPolicy ByPass -c "irm https://raw.githubusercontent.com/sinolion/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 ls --tag rocm                 # every AMD machine
fleet top                           # live view, like htop for the whole fleet
fleet show gpu-box                  # one machine in detail: jobs, software, models, folders
fleet ps                            # every job on every GPU, and which GPUs are idle
fleet models                        # every model being served, and how to reach it
fleet edit gpu-box --path models=/data/models   # where that machine keeps its models
fleet ssh gpu-box -- nvidia-smi     # run something there
fleet add "ssh ubuntu@10.0.0.7"     # add a machine
fleet ls --discover                 # machines in your ssh config and on your tailnet
fleet doctor nas                    # why a machine will not let you in, and the fix

Where a machine keeps its models, datasets and media is written on the machine itself, in machine.yaml (fleet edit NAME --path models=/data/models). Whoever looks at that machine reads the same answer, and the folder sizes and free space come with every probe.

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.

ssh + nvidia-smi

nvitop / gpustat

all-smi / gpuwho

SkyPilot / dstack

fleet

All your machines in one view

✗

✗ one machine

✓

✓ the ones it manages

✓

Built for coding agents (skill / MCP)

✗

✗

✗

partly

✓

Nothing installed on target machines

✓

✗

gpuwho ✓, all-smi ✗

✗

✓

Jobs, served models, software, data folders

✗

jobs, one machine

jobs

✗

✓

NVIDIA, AMD and Apple GPUs

NVIDIA

NVIDIA

all-smi ✓

✓

✓

Launches new cloud VMs

✗

✗

✗

✓

✗

History, alerts sent to you

✗

✗

all-smi ✓

partly

✗ alerts when asked

When to use something else. To rent GPUs on demand at the lowest price, use SkyPilot or dstack: they launch and stop machines, and fleet does not. For weeks of metrics and paging on a large cluster, use DCGM with Prometheus and Grafana. For a live dashboard of many accelerator kinds (Gaudi, NPUs), use all-smi. fleet is for the machines you already have, and for letting your agent use them.

Why not just Tailscale, Ansible, or an ~/.ssh/config? Use them with fleet, not instead of it. Tailscale connects your machines, and fleet runs over it happily, but it does not tell your agent which machine has a free GPU. Ansible changes machines to match a playbook you write, and has no idea what is busy right now. An ~/.ssh/config names your hosts, and fleet reads it. fleet is the part in between: what you have, what is free on it, what is running and installed there, in a form your agent can use without you.

FAQ

Setting up

No. Install it where you use it: the machine you work from, and any other machine where you also run agents. The machines you only use — GPU servers, rentals, a NAS — need SSH and nothing else.

No. fleet uses whatever SSH reaches your machines: a LAN, a VPN, a jump host, a rental's public port. If you have Tailscale, fleet ls --discover finds your tailnet machines for you, and Tailscale SSH decides who may log in where — fleet just connects. See Reaching your machines.

They do not need to: each one looks at the machines its own SSH reaches, and what a machine says about itself — its cost, tags, where its models live — is kept on that machine, so both read the same. The machines you added by hand are in one file, machines.yaml (fleet paths shows where); copy it, or keep it in your dotfiles.

Yes — that is the normal case. fleet is installed once per machine: one command, one list of machines. Each agent only gets a small skill or MCP entry pointing at it, so Claude Code, Codex, Gemini CLI and a desktop app all see the same machines, and can use them at the same time. Install a new agent later? Ask an agent that has fleet to run fleet setup.

Agents that can run commands (Claude Code, Codex, Gemini CLI, Copilot CLI, OpenCode, …) get a skill — text that tells them the fleet commands; it costs nothing until a task needs a machine. Apps that cannot (Claude Desktop, Cursor, VS Code, …) get an MCP server that runs the same commands for them. See Agents. After installing, start a new session so the agent loads it.

Safety

No and no. fleet has no key of its own and never handles a password: it runs ssh as you would. For a machine that only takes a password, it offers ssh-copy-id in your terminal, where you type the password into ssh itself, once. The agent runs fleet ssh NAME and never sees a key or a password; it may see a machine's address, as fleet show prints it.

Almost nothing: the notes file fleet edit writes there (machine.yaml: tags, cost, a note, folders, declared servers), a small cache of software versions and folder sizes in ~/.cache/fleet, and nothing at all in authorized_keys. No program, no service. What fleet changes has the full list.

It is told not to. Removing a machine is left to you, and is not available to apps over MCP at all. When a request is ambiguous — which machine, which user — the agent asks instead of guessing.

Machines

Some systems — containers, GPU rentals — show / as a small overlay while the space is on another volume. Tell fleet which paths to watch: "on gpu-box, watch /workspace", or fleet edit gpu-box --disk-path /workspace. See Disks.

Re-point it, keeping its name, tags, cost and history: "gpu-box is now at ssh -p 40123 root@5.6.7.8", or fleet edit gpu-box --ssh "ssh -p 40123 root@5.6.7.8".

fleet does not solve connectivity; it uses the routes you have. The machine you run fleet on must reach each machine over SSH; the machines never need to reach each other. For machines behind different NATs, put them on a mesh network such as Tailscale or ZeroTier and add them by their mesh address. See Reaching your machines.

Yes, both ways. A Windows machine works as a target with OpenSSH Server and nothing else, and fleet runs on Windows too. See Windows.

No service. fleet runs only when you or an agent use it. The ssh connection it opened to each machine stays open for two minutes after the command (on Linux and macOS), so the next one does not dial again, and then closes by itself. On a machine it looks at, a du of the folders you named may run in the background now and then, so their sizes are known without making a probe wait.

fleet stopped managing access: no center, no invites, no keys of its own. Upgrade, and add your machines again. Upgrading from 0.5 lists what 0.5 left on your machines and how to remove it.

fleet uninstall (--purge to delete its files too): it removes fleet from your agents and prints the last step, uv tool uninstall agents-fleet. See Removing fleet.

Learn more

Status: v0.6. 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.

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

MIT

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