cua (trycua/cua) is an open-source AI project on GitHub. Repository summary: 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). Its focus includes evaluation and observability, developer-centric engineering workflows, workflow automation. It is suitable for extension, integration, and iterative delivery in real workflows.
License
MIT
Stars
17,322
Homepage
https://cua.ai/Features
- Core capability: 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).
- Includes evaluation, tracing, or observability capabilities
- Built for code generation, debugging, or engineering integration
- Supports orchestrated automation flows and scheduling
- Repository: trycua/cua
- Primary language: HTML
Use Cases
- Used for AI quality monitoring and regression evaluation
- Supports AI engineering build-and-iterate workflows for dev teams
- Used for cross-system process automation and operations efficiency
- Build internal AI workflow prototypes with cua
- Validate cua in production-like engineering scenarios
- Building AI development workflows
FAQ
Teams should first define integration boundaries and call patterns, then map repository capabilities into concrete interfaces, parameters, and access rules. GitHub repository: https://github.com/trycua/cua. Community traction is around 17,320 stars. License: MIT.
It usually works as an execution component or capability layer, with common deployment fits such as: Used for AI quality monitoring and regression evaluation, Supports AI engineering build-and-iterate workflows for dev teams, Used for cross-system process automation and operations efficiency.
