Give AI agents computers they can use.
Cua provides open-source desktop automation, isolated cloud desktops, local macOS VMs, and benchmarks for evaluating computer-use agents.
- Cua Fleets: Provision a Linux desktop, run a command, and save a screenshot.
- Cua Driver: Operate Calculator and verify its result.
- Lume: Create a Tahoe VM and connect over SSH.
- Cua Bench: Create and verify a simulated task.
You bring the agent and model. Cua provides the computer and automation tools. Computer-Use 2.0 describes an agent moving between code, APIs, and graphical interfaces within the same task.
Two Cua Driver sessions select cells in LibreOffice Calc and objects in Inkscape on an Omarchy desktop while a terminal stays in the foreground. Watch the 50-second demo, then explore Omarchy on Fleet.
recording.mp4
Provision isolated cloud desktops at run.cua.ai. A Fleet maintains sandbox capacity; your code claims a desktop from a pool and uses the Sandbox SDK to run commands, capture screenshots, and interact with apps inside it.
Your first result: provision a Linux desktop, run uname -a, save a screenshot, and delete the cloud resources. The tutorial covers Fleet credentials, dependencies, and cleanup. Pools can retain paid capacity after a claim ends, so follow its cleanup steps.
Local sandboxes and Fleets share the Sandbox SDK, but credentials, images, operations, and runtime requirements differ. Use the runtime support reference to choose an environment. For your own hardware, see Manage local sandbox lifecycle.
Your first Cloud Fleet | Fleet overview | Sandbox SDK reference
Give your agent tools to inspect and operate native desktop apps and browsers on macOS, Windows, and Linux. Connect through the CLI, MCP, or typed SDKs. Background delivery lets agents work without moving your pointer or taking focus when the app and platform support it; see platform support for the boundaries.
macOS / Linux
/bin/bash -c "$(curl -fsSL https://cua.ai/driver/install.sh)"Windows (PowerShell)
irm https://cua.ai/driver/install.ps1 | iexYour first result: connect your agent, ask it to compute 6 × 7 in Calculator, and have it verify that the app displays 42. The tutorial covers platform setup, permissions, and agent connection.
Drive your first app | Installation | CLI Reference
Using Claude Code, Codex, Cursor, OpenClaw, or another agent? Find your integration. Source documentation and architecture notes live in libs/cua-driver/README.md.
Create and manage local macOS and Linux VMs on Apple Silicon using Apple's Virtualization.Framework.
/bin/bash -c "$(curl -fsSL https://cua.ai/lume/install.sh)"Your first result: create a vanilla macOS Tahoe VM from an Apple restore image, start it, and connect over SSH. The tutorial uses the Lume CLI directly and explains the unattended setup defaults.
Create your first Lume VM | Installation | CLI reference
Build computer-use tasks, evaluate agents, and export trajectories for training. Start with a simulated task that requires no VM, Docker, or model API key.
With Python 3.12 or 3.13 and uv installed:
uv tool install 'cua-bench[browser]'
uv tool run --from 'cua-bench[browser]' playwright install chromiumYour first result: create a small task, run its reference solution, and verify that its evaluator reports a reward of 1.0. Then try the same task yourself.
Build your first task | What is Cua-Bench? | CLI reference | Partner with us
- Documentation — Guides, examples, and API reference
- Blog — Tutorials, updates, and research
- Discord — Community support and discussions
- GitHub Issues — Bug reports and feature requests
- Security — Private vulnerability reporting
If Cua supports your research, please cite the software:
@software{cua2025,
author = {{Cua AI, Inc.}},
title = {Cua},
year = {2025},
url = {https://github.com/trycua/cua},
license = {MIT}
}For reproducibility, include the Cua release or commit used in your experiments. Citation metadata is also available in CITATION.cff.
We welcome contributions! See our Contributing Guidelines for details.
MIT License — see LICENSE for details.
Third-party components have their own licenses:
- Kasm (MIT)
- OmniParser (CC-BY-4.0)
- Optional
cua-agent[omni]includes ultralytics (AGPL-3.0)
Apple, macOS, Ubuntu, Canonical, and Microsoft are trademarks of their respective owners. This project is not affiliated with or endorsed by these companies.
Thank you to all our GitHub Sponsors!
| Adam Cohen Hillel | CodeRabbit | Zephyr Cloud IO |
|---|---|---|