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Open-source infrastructure for Computer-Use Agents. Sandboxes, SDKs, and benchmarks to train and evaluate AI agents that can control full desktops (macOS, Linux, Windows).

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Cua logo

Build, benchmark, and deploy agents that use computers

cua.ai Discord Twitter Documentation
trycua%2Fcua | Trendshift

CuaBot - Co-op computer-use for any agent

cuabot gives any coding agent a seamless sandbox for computer-use. Individual windows appear natively on your desktop with H.265, shared clipboard, and audio.

npx cuabot                 # Setup onboarding
# Run any agent in a sandbox
cuabot claude              # Claude Code
cuabot openclaw            # OpenClaw in the sandbox

# Run any GUI workflow in a sandbox
cuabot chromium
cuabot --screenshot
cuabot --type "hello"
cuabot --click <x> <y> [button]

Get Started | Installation | First spotted at ClawCon

cuabot screenshot
cuaXclawdbot_nbg

Beyond cuabot — explore our SDKs, benchmarks, and sandboxes for your own computer-use agents.

Choose Your Path


Cua - Agentic UI Automation & Code Execution

Build agents that see screens, click buttons, and complete tasks autonomously. Run isolated code execution environments for AI coding assistants like Claude Code, Codex CLI, or OpenCode.

# Requires Python 3.12 or 3.13
from computer import Computer
from agent import ComputerAgent

computer = Computer(os_type="linux", provider_type="cloud")
agent = ComputerAgent(model="anthropic/claude-sonnet-4-5-20250929", computer=computer)

async for result in agent.run([{"role": "user", "content": "Open Firefox and search for Cua"}]):
    print(result)

Get Started | Examples | API Reference


Cua-Bench - Benchmarks & RL Environments

Evaluate computer-use agents on OSWorld, ScreenSpot, Windows Arena, and custom tasks. Export trajectories for training.

# Install and create base image
cd cua-bench
uv tool install -e . && cb image create linux-docker

# Run benchmark with agent
cb run dataset datasets/cua-bench-basic --agent cua-agent --max-parallel 4

Get Started | Partner With Us | Registry | CLI Reference


Lume - macOS Virtualization

Create and manage macOS/Linux VMs with near-native performance on Apple Silicon using Apple's Virtualization.Framework.

# Install Lume
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/trycua/cua/main/libs/lume/scripts/install.sh)"

# Pull & start a macOS VM
lume run macos-sequoia-vanilla:latest

Get Started | FAQ | CLI Reference


Packages

Package Description
cuabot Multi-agent computer-use sandbox CLI
cua-agent AI agent framework for computer-use tasks
cua-computer SDK for controlling desktop environments
cua-computer-server Driver for UI interactions and code execution in sandboxes
cua-bench Benchmarks and RL environments for computer-use
lume macOS/Linux VM management on Apple Silicon
lumier Docker-compatible interface for Lume VMs

Resources

  • Documentation — Guides, examples, and API reference
  • Blog — Tutorials, updates, and research
  • Discord — Community support and discussions
  • GitHub Issues — Bug reports and feature requests

Contributing

We welcome contributions! See our Contributing Guidelines for details.

License

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)

Trademarks

Apple, macOS, Ubuntu, Canonical, and Microsoft are trademarks of their respective owners. This project is not affiliated with or endorsed by these companies.


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Thank you to all our GitHub Sponsors!

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Open-source infrastructure for Computer-Use Agents. Sandboxes, SDKs, and benchmarks to train and evaluate AI agents that can control full desktops (macOS, Linux, Windows).

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