OMAR: Open-Source TUI for Managing Hundreds of AI Coding Agents Hierarchically

OMAR (Open Multi-Agent Runtime) is a TUI (terminal user interface) for orchestrating large numbers of AI coding agents in parallel. Created by Karim and Shaokai after being impressed by Claude Code's ability to fix CI issues overnight, they built it to replace the pain of Ctrl+Tab through multiple Claude Code windows. The project is open-source and available at omar.tech.
Key Features
- Deep hierarchies: Agents managing agents, like a company. Create parallel organizations of arbitrary depth.
- Heterogeneous backends: Let Claude, Codex, Cursor, and Opencode collaborate as a team. Mix and match the best model for each task.
- Full control: Talk to and control any subagent. Navigate hierarchies with arrow keys and attach via popup.
- Flexible lifespans: Long-running or ephemeral agents, persistent state across sessions with memory snapshots.
- Messaging & integrations: Connect agents to Slack channels.
- Built on tmux: Supports all tmux commands and key bindings. Highly customizable.
Quick Start
One-liner (macOS/Linux):
$ curl -fsSL https://omar.tech/install.sh | sh
Homebrew:
$ brew install lsk567/omar/omar
From source (requires Rust 1.70+ and GNU Make):
$ git clone https://github.com/lsk567/omar.git
$ cd omar && make install
Prerequisites
tmux 3.0+ and at least one agent backend: Claude Code, Codex CLI, Opencode, or Cursor CLI.
Usage
- Launch:
$ omar - Copy a prompt into your Executive Assistant window. Agents will spawn and organize hierarchically.
The idea is to move from single-agent terminals to a swarm that mirrors organizational structures — an Executive Assistant delegates to teams, which delegate to subagents. All controllable from one TUI.
📖 Read the full source: HN AI Agents
👀 See Also

OpenClaw A2A Plugin: Direct Agent-to-Agent Messaging Over the Internet
An OpenClaw A2A plugin enables direct file and message transfer between OpenClaws and other agents over the internet without third-party services like WhatsApp or email.

Reduce AI Coding Session Costs by 90% with Graph-Based Code Indexing
A developer built a local graph database that indexes a codebase using LLM-generated summaries, cutting Claude Code session costs from $6-10 to cents by avoiding redundant file re-reads.

MCP Server for Local XMind Mind Map Files Released
A developer has published an MCP server that provides 22 tools for reading and writing local XMind mind map files. The server works with MCP-compatible AI clients like Claude Desktop and Cursor.

SpruceChat Runs 0.5B LLM On-Device on Miyoo Handhelds via llama.cpp
SpruceChat runs Qwen2.5-0.5B entirely on-device on handheld gaming devices using llama.cpp, with no cloud or WiFi required. On a Miyoo A30 (Cortex-A7 quad-core), it loads in ~60 seconds and generates at ~1-2 tokens/second.