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cua
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cua

Active·★ 31.1k·MIT·Updated 2026-10-27
★ Most Popular★ Essential★ Trending

Cua gives AI agents computers they can use. Rather than being an agent itself, it provides the environment and controls: Cua Spaces gives agents full desktops (local macOS VMs on a Mac, or Linux images) on machines you own; Cua Driver lets agents inspect and operate native apps and browsers on macOS, Windows and Linux through a CLI, MCP or typed SDKs; Lume creates macOS and Linux VMs on Apple Silicon; and Cua Bench creates simulated tasks to evaluate agents and export trajectories.

It suits teams building or evaluating computer-use agents who need isolated, reproducible machines, and developers who want their coding agent (Claude Code, Codex, Cursor or OpenClaw) to operate desktop apps safely. Sandboxes can be created from the `cua` CLI or from SDKs in Python, TypeScript, Swift and Kotlin, and Cua Driver can work in the background without taking over your pointer. Spaces adds features such as moving a signed-in app into a sandbox and sharing a desktop between you and an agent.

Getting started: run `curl -fsSL https://cua.ai/install.sh | sh` on macOS or Linux (PowerShell on Windows). The installer sets up the `cua` CLI, the Spaces app on macOS 26+ and the Cua Driver MCP and skill; then `cua sb create ubuntu --name dev` creates a sandbox.

This write-up is based on the project's README and public repository data. We have not hand-tested the tool. Data as of 2026-10-24.

License
MIT
Latest release
cua-sdk-v0.9.0 · 2026-10-24
Last commit
2026-10-24
Contributors
155
Forks
2,251
Open issues and PRs
1,271
First published
2025-01-31

Source: GitHub, npm and PyPI public APIs.

#AI Agents#Virtualization#UI Automation#Benchmarking#Code Execution#Coding#Data Analysis
$ Install
$ curl -fsSL https://cua.ai/install.sh | sh
↗ Visit site★ GitHub
01

Features

01Build AI agents for desktop UI automation and interaction.
02Provide isolated code execution environments (sandboxes).
03Benchmark computer-use models with standardized tasks.
04Train agents using reinforcement learning environments.
05Manage high-performance macOS/Linux VMs on Apple Silicon.
02

Why choose it

+Isolated desktops, VMs and containers keep computer-use agents away from your main system.
+Works with any agent and model through CLI, MCP and SDKs in four languages.
+Includes benchmarking tools for evaluating agents and generating training data.
+Core SDK, CLI, Driver and Lume are MIT licensed.
03

Trade-offs

!Licensing is mixed: Cua Spaces is source-available under FSL-1.1-MIT rather than open source, and some optional components are AGPL.
!The Spaces app requires macOS 26 or later; local macOS VMs require Apple Silicon.
!The installer signs you in to a Cua account by default, and some features target paid plans that are still being introduced.
05

Maintenance check

ActiveChecked: 2026-10-23
Last commit
2026-10-23
Commits, last 90 days
100+
Releases, last 90 days
30
Latest release
cua-spaces-v0.13.1 (2026-10-22)
Open issues
1247
Recent issues with at least one comment
1/12

Status rule: archived on GitHub = Archived; last commit within 90 days = Active; 91 to 365 days = Slowing; older = Stale. All figures come from the GitHub API on the date shown.

Most discussed open issues

  • #353 An error because the Docker image trycua/cua-ubuntu:latest doesn't have a version compatible with arm64 arch (Apple Silicon Mac)13 comments · 2025-08-19
  • #3550 [RFC]: Isolated background input on Hyprland12 comments · 2026-09-05
  • #22 Document how to publish a lume VM image to a custom GHCR registry12 comments · 2025-02-08
  • #3971 Feature request: configurable post-action observation and text-field settle delays in MCP10 comments · 2026-09-18
  • #3796 [RFC]: cooperative cancellation of one in-flight driver call, with owned native cleanup10 comments · 2026-09-13

Issue titles are quoted from GitHub. Open the link to check whether a problem still applies to the version you use.

04

Who it fits

Pick it if
  • You are building Computer-Use agents and need robust, self-hostable isolated desktop/VM sandboxes (Docker, QEMU, Apple Vz).
  • You need native app operating drivers, standardized benchmarking harnesses, and secure isolation for autonomous agent task execution.
Look elsewhere if
  • You only need simple UI macros on your personal physical machine (Windows-MCP or local desktop helpers are easier).
  • Your agents interact solely via text APIs, shell commands, or databases and have no need for a virtual graphical desktop.
06

How it differs

Windows-MCP logovs Windows-MCP★ 10.5k

CUA provides sandboxed virtual desktops (QEMU/Docker) for safe agent testing; Windows-MCP controls the user's host physical Windows machine directly.

Full comparison →
mcp-server-browserbase logovs mcp-server-browserbase★ 3.4k

CUA simulates full operating system environments for any desktop app; Browserbase specializes in managed cloud browser instances strictly for web automation.

Full comparison →
07

Compatibility

Docker
Native Sandbox
Verified via docs
QEMU
Native Sandbox
Verified via docs
Apple Virtualization.Framework
Native Sandbox
Verified via docs
Linux
Target OS
Verified via docs
macOS
Target OS
Verified via docs
Apple Silicon
Optimized Host
Verified via docs
08

Quick start

1
$ curl -fsSL https://cua.ai/install.sh | sh
09

Use cases

↳Developing and deploying AI agents for autonomous desktop interaction and task completion.
↳Creating secure, isolated code execution environments for AI coding assistants and development workflows.
↳Benchmarking and training computer-use agents using standardized tasks and reinforcement learning.
10

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On this page
01Features02Why choose it03Trade-offs05Maintenance check04Who it fits06How it differs07Compatibility08Quick start09Use cases10Alternatives
trycua /
cua
↗

Sandboxed desktops and drivers for computer-use agents

31.1k2.3kMIT
Last commit1d ago
StatusActive
CategoryLLM Infra
Contributors155
Latest releasecua-sdk-v0.9.0
Links
Documentation↗Discussion↗Issues↗Releases↗
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