Run a team of coding agents
on your GPU server
Claude Code, Codex, and 40+ coding agents, running where your GPUs are.
Start them at your desk, steer them from your phone.

One workspace for your experiments
Drive the agents on your remote server, review what they did, and steer any of them, from your desktop or your phone.
Drive the server your GPUs run on
Connect your GPU server, cluster nodes, or a cloud VM and drive the agents running on it through Vicoa. No SSH gymnastics, no VNC round-trip.
- Your code and checkpoints stay on your own server
- Reach every machine from your phone, laptop, or the web
Instead of SSH in every time you want to check a run
Steer agents from your phone
Pick up the exact same session on your phone, approve a step, or redirect the agent, and it syncs everywhere instantly.
- Approve the risky or expensive step from anywhere
- Catch a broken run at 6pm, even when you are not at your desk
Instead of being chained to the terminal at your desk
Agent team for parallel idea validation
Run several agents at once: one tries a new approach, another runs an experiment, another digs into the analysis.
- Explore several ideas at once, each isolated on its own branch
- See which agent is running, blocked, or done at a glance
Instead of one agent, one idea, one experiment at a time
Analyze your results
Open the file tree beside the conversation to inspect logs, metrics, checkpoints, and plots, then ask the agent to dig into what they show.
- Browse outputs and artifacts without a separate transfer
- Point the agent at a result and have it take the next step
Instead of scp-ing files back just to look at them
Review what the agent changed
Review every change as an inline git diff with word-level highlights, then flip to the files it touched or the terminal it ran, all in one view.
- Per-file diffs and commit history
- Verify the change instead of trusting a summary you can’t check
Instead of trusting a summary you can’t verify
A real terminal, on the server
Run commands, tail training logs, and watch a job in a live terminal on the same machine the agent uses.
- Full shell access without leaving the session
- Keep jobs, servers, and logs running while the agent works
Instead of juggling a second stack of SSH tabs
Cloud GPUs, lab servers, or your own hardware
Vicoa runs anywhere you can run a coding agent, and your codebase never leave that machine.
Lab & cluster
Your lab’s GPU server, or a node on the cluster.
Cloud VMs
Lambda, RunPod, Vast.ai, AWS, GCP, or Azure.
Your own hardware
A workstation or desktop at home.
From your server to your phone
Point Vicoa at the machine your experiments run on, in three steps
Install on your server
Install the Vicoa CLI on your lab server or cloud VM and sign in, and it auto-detects the coding agents already installed there.
Prefer the terminal?
Run experiments in parallel
Start agents on the server, each on its own git worktree, and see every session in one workspace.
Your phone is the remote control
Approve changes, review diffs, and steer your agents from anywhere.
Get The Mobile App
Install Vicoa on iPhone or Android
Open the same coding sessions from your phone with a real mobile app, not a terminal.
Already living in SSH + tmux?
Keep it. tmux keeps your session alive when you disconnect. Vicoa adds the workspace around it: run agents in parallel, review their work, and steer them from any device, at your desk or away from it.
What tmux does
Keeps your session alive.
- Your job keeps running after you disconnect
- Reattach from the same terminal
What Vicoa adds
Desk or awayA full workspace for your agents, on any device.
- Run many agents in parallel, in one view
- Review diffs, logs, and results as they land
- Steer and approve from your desk or your phone
- Get pinged when a run finishes or needs you
Who it’s for
ML & AI researchers
Training runs, evals, and demos on a remote GPU server, kicked off and steered without living in a terminal.
PhD & master’s students
Your experiments run on the lab cluster or a cloud VM; check on them and nudge them between classes, from any device.
Data scientists
Iterate on pipelines and models where the data and compute already are, and review the agent’s changes easily.
Labs & PIs
Equip the whole lab. When your students run more experiments and spend less time babysitting them, your lab produces more.
Loved by researchers
Frequently Asked Questions
Answers for researchers running agents on remote machines
















