CLI Agent Orchestrator (CAO) orchestrates multiple AI agent sessions within tmux terminals. It supports hierarchical multi-agent systems with a supervisor coordinating worker agents to solve complex problems by delegating tasks. CAO facilitates multi-agent collaboration through the Model Context Protocol (MCP) server, enabling seamless communication and parallel processing.
CAO offers hierarchical orchestration, session-based isolation, and intelligent task delegation. Its flexible workflow patterns support both sequential and parallel processing, and it includes features like scheduled runs and context preservation. It also features direct worker interaction and steering, allowing real-time guidance. The allowedTools feature offers fine-grained control over agent capabilities, and advanced CLI integration leverages features from tools like Claude Code and Amazon Q Developer.
- Hierarchical Orchestration: Supervisor agents coordinate workflow management and task delegation to specialized worker agents.
- Session Isolation: Each agent runs in isolated tmux sessions, ensuring context separation.
- Flexible Workflow Patterns: Supports sequential and parallel coordination for optimization of development speed and quality.
- Context Preservation: Supervisor provides only necessary context to worker agents to avoid pollution.
- Tool Restrictions: Control agent capabilities via
roleandallowedToolsfor enhanced security and control. - Advanced CLI Integration: Leverages features from external CLI tools like Claude Code and Amazon Q Developer.
- Scheduled Runs: Automate workflows using cron-like scheduling for routine tasks and monitoring.
CAO is actively developed with recent commits and ongoing issue resolution. Comprehensive documentation and a growing community presence indicate increasing maturity and reliability. It supports several prominent CLI agents, highlighting its adaptability, but ongoing feature development ensures continued evolution and enhancement.
CAO benefits developers and researchers needing to manage and coordinate multiple AI agent workflows. It streamlines complex tasks by dividing workloads and enabling collaboration. It provides a structured approach to orchestration, improving efficiency and facilitating consistent results compared to manual approaches or ad-hoc agent usage.