Cua: Scale Computer Fleets for Computer-Use Agents

Introduction

Cua is an open-source tool built for managing large-scale computer fleets, designed to help developers and operations teams efficiently schedule and control AI agents that operate in computer-use scenarios. Whether on Linux, Windows, macOS, or Android devices, Cua provides a unified interface that lets you manage thousands of machines as easily as if they were a single system. With support for MCP (Multi-Computer Protocol) and CLI (Command-Line Interface), Cua delivers the foundational infrastructure needed for automation tasks, distributed testing, and AI-driven computer interaction.

Key Features

• Cross-platform fleet management: Seamlessly supports Linux, Windows, macOS, and Android devices, enabling unified control across mixed architectures.
• Dual MCP/CLI interfaces: Provides a standardized Multi-Computer Protocol (MCP) and Command-Line Interface (CLI) for easy integration into existing CI/CD or automation workflows.
• Computer-use agent orchestration: Purpose-built for AI agents that need to "operate a computer," supporting remote GUI actions, file read/write, process management, and other complex tasks.
• Open source and extensible: Fully open source, allowing developers to create custom plugins, connectors, or protocol extensions to meet specific business needs.
• Real-time status monitoring: Built-in cluster health checks and log aggregation help quickly pinpoint faulty nodes or performance bottlenecks.

Highlights

• Simplified large-scale management: Skip the hassle of configuring machines one by one—define behavior policies for the entire cluster with a single configuration file.
• Native agent ecosystem support: Deep compatibility with mainstream AI frameworks like LangChain and AutoGPT, enabling computer-use agents to operate multiple devices just like a human would.
• Lightweight and high performance: Core components are written in Rust, with extremely low memory usage, maintaining millisecond-level response times even when managing thousands of nodes.
• Security first: All communication is encrypted with TLS, and role-based access control (RBAC) ensures cluster operations cannot be tampered with by unauthorized parties.
• Community-driven development: An active GitHub community provides rich examples, documentation, and a plugin marketplace to accelerate problem-solving and feature expansion.

Who It's For

DevOps engineers who need to manage mixed-OS clusters and want to integrate computer automation into their pipelines; AI application developers building intelligent agents that require remote computer control (such as browser automation, desktop app testing, or data collection bots); system administrators managing hundreds of Android devices or IoT endpoints who need centralized command dispatch and result collection; and research or educational institutions looking to set up distributed experiment environments or use Cua as a teaching and experimentation platform for computer-use agents.