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Cua is a cloud desktop platform designed specifically for computer-use AI agents. Built by a team focused on agent infrastructure, Cua solves the problem of providing scalable, reproducible environments for agents that need to interact with graphical user interfaces. The platform offers cloud sandboxes for macOS, Windows, Linux, and Android, allowing agents to run on any operating system at scale. Core capabilities include booting cloud desktops, opening live GUI sessions, controlling mouse and keyboard, and executing bash commands. Cua also supports environment configuration, snapshotting, and forking into parallel runs, making it ideal for testing and development workflows. Trusted by over 50,000 engineers at companies like Hugging Face, Datadog, Meta, and NVIDIA, Cua fits seamlessly into CI/CD pipelines, agent development, and multi-platform testing. It is particularly suited for developers building computer-use agents with frameworks like Claude Code, Codex, and OpenClaw.
4.5/5
High, consistent, and reliable
Clean and developer-focused
To provide cloud-based desktop environments for AI agents to interact with GUIs programmatically.
Works with macOS, Windows, Linux, and Android; integrates with Claude Code, Codex, OpenClaw, and any computer-use agent via CLI and API.
Freemium with paid tiers for higher usage and advanced features
Features with the highest value for users are highlighted here.
Multi-OS sandboxes (macOS, Windows, Linux, Android)
CLI and API for agent control
Snapshot and fork environments
Prebuilt images for computer-use agents
Live GUI session via VNC
Custom dependency configuration
Parallel run forking
Scalable cloud infrastructure
Use the CLI command 'cua sb launch ubuntu' to spin up a sandbox with your chosen OS.
Connect to the desktop via VNC using 'cua sb vnc <session-name>' to view and interact with the GUI.
Use 'cua sb shell <session-name>' to run bash commands, or programmatically control mouse and keyboard via API.
Save the environment state with 'cua sb snapshot <session-name>' and fork into multiple parallel clones for testing.
AI Agent Developers
DevOps Engineers
QA Engineers
Machine Learning Researchers
Startups
Enterprise IT Teams
Open Source Contributors
Freelance Developers
Educational Institutions
Hobbyists
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