cua (trycua) Review 2026: Open-Source Infrastructure for Computer-Use AI Agents

Computer-use AI agents — agents that can see a screen and control a desktop — are one of the most exciting frontiers in applied AI. Building and evaluating these agents reliably requires specialised infrastructure: sandboxed environments, robust SDKs, and standardised benchmarks. cua by trycua provides all of this as open-source software.

What Is cua?

cua is an open-source infrastructure project developed by trycua on GitHub. It provides everything needed to build, run, and evaluate AI agents that can control full desktop environments — not just web browsers, but native applications on macOS, Linux, and Windows.

The name stands for Computer-Use Agent, and the project comprises several components: Cua (the agent SDK), Cua Drivers (tools for giving coding agents computer capabilities), Cua Bench (evaluation framework), and Lume (macOS VM management).

Key Features

Desktop Sandboxes

cua spins up isolated desktop environments — full operating systems running in VMs — that agents can control safely without affecting your host machine. This is essential for evaluating agents on tasks that involve real applications.

Cross-Platform Support

cua supports agents running on macOS, Linux, and Windows desktops. The same SDK and CLI work across all three platforms.

MCP Integration

cua provides the same CLI and MCP server on macOS and Windows, compatible with Claude Code, Cursor, Codex, and custom clients. This means you can use cua agents from your existing AI coding workflow.

Background Operation

Agents can drive native desktop applications in the background — clicking, typing, and verifying results without stealing the cursor or interrupting your work.

Benchmarking

The Cua Bench framework lets you evaluate computer-use agents on OSWorld, ScreenSpot, Windows Arena, and custom task sets. Evaluation trajectories can be exported for training new models.

Model Agnostic

cua works with any vision-capable AI model — Claude, GPT-4V, Gemini, and open-source alternatives.

Pros

• Free and open source
• Full desktop sandboxes — not just browser automation
• Cross-platform (macOS, Linux, Windows)
• MCP integration for Claude Code and Cursor
• Background operation without interrupting your workflow
• Built-in benchmarking for evaluating agents
• Model-agnostic

Cons

• Requires significant compute to run full desktop VMs
• Complex setup compared to browser-based automation tools
• Computer-use agents are still unreliable for complex tasks
• Best results require vision-capable frontier models (API costs)

Who Is It For?

cua is for AI researchers building and evaluating computer-use agents, developers who want to automate native desktop workflows with AI, and teams exploring agentic AI infrastructure. It is a technical tool for technical users.

Pricing

Free. Available at github.com/trycua/cua. API costs depend on your chosen model provider.

Verdict

cua is the most comprehensive open-source infrastructure available for building and evaluating computer-use AI agents. If you are working in this space — building agents, evaluating models, or automating desktop workflows — it is the best starting point available for free.

Rating: 8/10 — Best open-source computer-use agent infrastructure available. High technical complexity and compute requirements limit accessibility.

This article is for educational purposes only. Always evaluate open-source tools against your own requirements before deploying to production.