Cua: Cross-OS Computer Use and Virtualization Platform
Scale computer-use 2.0 with open-source drivers, cross-OS fleets, and benchmarks.
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What does this agent do, and when should you use it?
Cua is an open-source toolkit for building and evaluating AI agents that operate desktop applications. It comprises four main components: Cua Drivers provide background GUI automation on macOS, Windows, and Linux, allowing agents to control native apps without stealing the cursor or focus; Cua Sandbox offers isolated VM/container sandboxes across multiple operating systems (Linux, macOS, Windows, Android) via a unified API; Cua Bench provides benchmarks and RL environments such as OSWorld, ScreenSpot, and Windows Arena; and Lume manages macOS/Linux VMs on Apple Silicon using Apple's Virtualization.Framework. The project is MIT-licensed and includes CLIs, an MCP server, and a Python SDK.
Cua enables computer-use agents by: using Cua Drivers to operate native desktop apps in the background on macOS, Windows, and Linux (click, type, verify), with integration via CLI and MCP server for clients like Claude Code, Cursor, and Codex; using Cua Sandbox to spin up ephemeral sandboxes of VMs or containers, providing shell execution, screenshots, mouse/keyboard control, and mobile gesture APIs; using Cua Bench to run standardized benchmarks and export trajectories; and using Lume to create and manage macOS/Linux VMs with unattended installation.
- A developer uses Cua Drivers with Claude Code to let a coding agent operate native macOS apps in the background, such as testing a GUI application.
- A data scientist creates a Cua Sandbox to run an isolated environment of any OS for automated data scraping or UI testing scripts.
- An AI researcher uses Cua Bench to evaluate their own agent on OSWorld or ScreenSpot benchmarks and export trajectories for training.
- A system administrator uses Lume to quickly deploy macOS VMs on Apple Silicon Macs for testing or CI.
- An automation engineer uses Cua's multi-OS support to run Windows-specific apps in a Windows sandbox while controlling from Linux.
What are this agent's strengths and limitations?
- Background operation of native apps without stealing cursor/focus, enabling multitasking agents.
- Unified API across macOS, Windows, Linux, and Android reduces cross-platform complexity.
- Includes benchmarks and RL environments for evaluating and training agents.
- Leverages Apple Virtualization.Framework for near-native performance in macOS VMs.
- macOS VM management relies on Apple Silicon (hardware constraint), limiting usability on other hardware.
- Windows support depends on PowerShell and possibly sandbox configuration; Wayland support is limited to specific compositors with explicit limits.
- Cloud services (cua.ai) are commercial; local QEMU path requires self-managing resources.
- Some components (e.g., cua-agent's omni option) depend on third-party licenses (AGPL-3.0), which may affect compliance.
How do you install or deploy this agent?
Installation varies by component:
- Cua Drivers (macOS/Linux): run bash -c "$(curl -fsSL https://cua.ai/driver/install.sh)"; Windows (PowerShell): irm https://cua.ai/driver/install.ps1 | iex.
- Cua Sandbox: pip install cua (requires Python 3.11+).
- Cua Bench: clone repo and use uv tool install -e ..
- Lume: run bash -c "$(curl -fsSL https://cua.ai/lume/install.sh)".
How do you use this agent?
For Cua Drivers, after install, follow the post-install instructions (see docs for driving your first app). For Cua Sandbox, use Python:
from cua import Sandbox, Image
async with Sandbox.ephemeral(Image.linux()) as sb:
result = await sb.shell.run("echo hello")
screenshot = await sb.screenshot()
await sb.mouse.click(100, 200)For Lume, create and run a macOS VM:
lume ipsw
curl -L "$(lume ipsw | tail -n 1)" -o ~/Downloads/macos-tahoe.ipsw
lume create macos-tahoe --ipsw ~/Downloads/macos-tahoe.ipsw --unattended tahoe
lume run macos-tahoeHow does this agent compare with similar options?
Comparable to Microsoft's OmniParser for UI parsing (integrated as an optional dependency in Cua), but Cua provides a full computer-use stack including drivers, sandboxes, and benchmarks. Compared to macOS virtualization tools like UTM, Lume focuses on native performance and unattended automation on Apple Silicon.