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cua

Free

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).

AI ChatbotsFreeFree tier
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Type
Open Source
Founded
2025
Company
c/ua
Visit Website GitHub (15.6k stars)
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About cua

What is CUI? What is CUA? How can I integrate c/ua into my workflow? c/ua

Key Features

  • macOS & Linux containers on Apple Silicon
  • Near-native performance with Lume virtualization
  • Computer Use Interface (CUI) for automation
  • Computer-Use AI Agent (CUA) framework for RPA workflows
  • Multi-provider AI control
  • Cross-platform workflows
  • Docker-powered macOS virtual machines
  • MCP Server for running Agent from Cursor, Claude Desktop, and other MCP clients.

Use Cases

  • Automated interaction with macOS/Linux applications
  • Running agentic RPA workflows
  • Controlling computers through Claude directly
  • Automating tasks across operating systems
  • Running macOS virtual machines leveraging Docker

FAQ

What is Lume? What is CUI? What is CUA?

Key Features

macOS & Linux containers on Apple Silicon
Near-native performance with Lume virtualization
Computer Use Interface (CUI) for automation
Computer-Use AI Agent (CUA) framework for RPA workflows
Multi-provider AI control
Cross-platform workflows
Docker-powered macOS virtual machines
MCP Server for running Agent from Cursor, Claude Desktop, and other MCP clients.

Pros & Cons

Pros
  • Open-source and MIT-licensed, allowing self-hosting and customization
  • Supports four major operating system families (Linux, Windows, macOS, Android)
  • Background driver enables agent control without interfering with user session
  • Scalable warm pools reduce latency for parallel agent workloads
  • Provides both local runtime and cloud infrastructure (Cua Cloud)
  • SOC 2 Type I compliance with BYOC and on-prem options for enterprise
  • MCP server and CLI integrate easily into existing agent stacks (Cursor, Claude Desktop, etc.)
  • Active development and community with regular releases and benchmarks
Cons
  • Currently in early access for larger deployments; smaller teams may face onboarding delays
  • Cloud macOS fleets rely on patented virtualization and may have limited availability
  • Onboarding was paused on previous infrastructure; new stack still rolling out gradually
  • Documentation and examples are still evolving as the platform matures
  • No explicit pricing for Cua Cloud services (likely pay-per-use for cloud resources)

Best For

Automated interaction with macOS/Linux applicationsRunning agentic RPA workflowsControlling computers through Claude directlyAutomating tasks across operating systemsRunning macOS virtual machines leveraging Docker

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