multi-agent-shogun
multi-agent-shogun is an open-source CLI tool that orchestrates multiple AI coding agents in parallel using a samurai-inspired hierarchy. It leverages tmux to manage terminal sessions, enabling a shogun (commander) to coordinate karo (elders) which in turn manage ashigaru (foot soldiers) - the actual AI agents. This design allows for running up to 10 agents simultaneously without any API cost for the coordination itself, as all inter-agent communication happens locally through tmux buffers. The tool supports popular AI coding assistants like Claude Code, OpenAI Codex, GitHub Copilot, and Kimi. By assigning tasks to multiple agents in parallel, it can accelerate code generation, debugging, and review processes. The hierarchical structure ensures organized task delegation and result aggregation, mimicking a feudal chain of command. Designed for developers and AI researchers, multi-agent-shogun enables experimentation with multi-agent systems in a lightweight, terminal-based environment. Since the coordination is done via tmux, there is no need for additional server infrastructure or paid orchestration services, making it an accessible option for comparing outputs from different AI models on the same coding task. While still in early development, the project demonstrates a novel approach to agent orchestration by combining system-level process management with a clear organizational metaphor. It is particularly suited for use cases like parallel code generation, multi-perspective code review, and automated testing across different AI models.
- Category
- AI Agents
- Pricing
- Open Source
Problem solved
It addresses the challenge of coordinating multiple AI coding agents without incurring API costs for inter-agent communication, by using a local tmux-based hierarchy that manages parallel execution and result aggregation.
Use cases
- Parallel code generation using multiple AI models
- Automated multi-agent code review
- Comparative analysis of AI coding assistant outputs
- Distributed debugging across agents
- Multi-model test generation
Audience
- Developers
- ML Engineers
- Data Scientists
- Researchers
Pros
- Zero coordination API cost
- Supports multiple AI models (Claude Code, Codex, Copilot, Kimi)
- Parallel execution via tmux for up to 10 agents
- Simple hierarchical orchestration model
- Open source and lightweight
Cons
- Limited to tmux environment (Unix-based systems)
- Hierarchical model may be complex for simple tasks
- Only supports a specific set of AI agents
- Lack of built-in error recovery or fault tolerance
- Minimal documentation and community support
Official website: https://github.com/yohey-w/multi-agent-shogun
Canonical LambdaBase page: https://www.lambdabase.com/tools/multi-agent-shogun