# What you will learn

• What Cezar is and the concrete problem it solves for developers running multiple AI coding agents.
• How to install and start it locally or on your own server with real commands.
• A small example of launching Claude Code, Codex and another agent in parallel.
• Where Cezar falls short today, and whether you should adopt it now or wait.

# What is Cezar, and why would you want it?

Cezar, published on GitHub as open-mercato/cezar, is an open-source orchestrator and agent development environment — an ADE — for running AI coding agents in parallel. The agents it targets include Claude Code, Codex, OpenCode, Pi and others in the same family. You can run it on your laptop for a quick session or leave it running 24/7 on your own server. It is written in TypeScript and is still a young project, not a mature platform. According to GitHub Trending, the repository appeared on the trending list with a modest star count, which tells you it is early rather than battle-tested.

The problem it addresses is real. If you have used Claude Code or Codex for anything beyond a single file, you know the workflow gets messy fast. One agent works in one terminal. A second agent needs its own terminal, its own working directory, and its own way of reporting back. When you want three agents working on three branches at once, you end up juggling windows, copying prompts, and losing track of which agent changed what. Cezar's pitch is that it becomes the control plane for all of them: one place to launch agents, watch their output, and keep their work isolated.

Who is it for? Developers who already run coding agents daily and want to scale from one to many without building their own harness. It is not for someone who has never used Claude Code — the value only shows up once you have multiple agents competing for your attention.

# How do you install and run Cezar?

Because Cezar is a TypeScript project distributed through GitHub, the standard path is to clone it and run it with your Node toolchain. The exact commands depend on the repository's current setup, so treat the following as the shape of the workflow rather than a guaranteed script:

git clone https://github.com/open-mercato/cezar.git
cd cezar
npm install
npm run start

For a 24/7 setup on your own server, you would run the same project on a machine that stays up and reach it remotely. That is the part that makes Cezar interesting: it is not tied to a hosted service. You own the box, you own the agents, and you own the logs. If your team has a spare server or a homelab machine, this is a natural fit.

Before you commit, check the repository's README for the current install steps and any required environment variables. Since the project is young, the setup may change between commits. That is normal for early open-source tools, but it means you should pin to a commit you have tested rather than pulling the latest blindly.

# What does running agents in parallel actually look like?

The core idea is simple. Instead of opening three terminals and typing three prompts, you register your agents with Cezar and give each one a task. Cezar then manages their execution side by side. A minimal mental model looks like this:

1. Start Cezar on your machine or server.
2. Add the agents you have installed — Claude Code, Codex, OpenCode, Pi, or another supported CLI.
3. Assign each agent a task, ideally scoped to a separate branch or directory.
4. Watch their output in one interface and review the resulting changes.

The parallelism is the point. One agent can refactor a module while another writes tests and a third updates documentation. Because they run as separate processes, a crash in one does not take down the others. That isolation is what makes the tool worth trying if you have ever had a single agent lock up your terminal mid-task.

The limitation is equally clear: parallel agents do not automatically coordinate. If two agents touch the same file, you will get conflicts. Cezar gives you the harness, but you still have to design the work split. Think of it as a traffic controller, not an autopilot.

# Should you adopt Cezar now, or wait?

Cezar is new. The repository is young, the star count is small, and the documentation is likely still catching up to the code. That does not make it useless — it makes it a tool for early adopters who are comfortable reading source and filing issues. If you want a polished product with support contracts, this is not it yet.

But the category is heating up. We have already covered agentbox, which runs dozens of Claude Code agents in parallel, and Codex-bridge, which gives ChatGPT local hands and agent muscle. The difference with Cezar is that it aims to be agent-agnostic and self-hosted. That combination — multiple vendors' agents, your own server, open source — is the gap it is trying to fill.

My advice: clone it, run it on a spare machine, and try two agents on two branches. If the workflow saves you even one context switch per hour, it has earned its place. If the setup fights you, come back in a few months. The project is early enough that the next few releases will decide whether it becomes infrastructure or a footnote.

For a broader view of how developers are rethinking the coding workflow around agents, see AI codes better than most devs — that was never the job.