shannhk/hermes-agent-control-room — explained in plain English
Analysis updated 2026-05-18
Set up a documentation based control room to organize how AI agents run on your own server.
Grow from one general purpose AI agent into a team of specialist agents for tasks like coding or SEO.
Add an orchestrator agent that routes tasks to the right specialist automatically.
Use bundled skills to provision a new server or audit its security settings.
| shannhk/hermes-agent-control-room | electron/governance | learnprompt/luban-skill | |
|---|---|---|---|
| Stars | 177 | 162 | 197 |
| Language | Shell | Shell | Shell |
| Setup difficulty | hard | easy | easy |
| Complexity | 4/5 | 1/5 | 2/5 |
| Audience | ops devops | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires setting up and managing your own VPS to host the agents this template organizes.
Hermes Agent Control Room is a starter template and organizational framework for people who want to run multiple AI agents on a server (VPS, a rented cloud computer) in a structured, scalable way. It is not itself an AI agent, it is the documentation, configuration templates, and runbooks (step-by-step operating guides) that govern the agents you set up. The core concept is to establish a central "control room", a folder of documentation that defines who your agents are, what they do, how they connect to each other, and how to recover when things go wrong. Once that foundation exists, you can grow from one general-purpose agent to a team of specialist agents (for example: one for SEO, one for coding, one for marketing, one for server operations) and optionally an orchestrator agent that routes work to the right specialist automatically. The template describes four levels of complexity: starting with one agent and the control room documentation, then adding specialist agents you talk to directly, then adding an orchestrator as a single front door, and finally automating recurring workflows. The key philosophy is to get the manual system working before adding automation. Bundled "skills" (reusable instruction sets for agents like Claude Code) cover tasks such as provisioning a new server, bootstrapping the full stack, managing the agent registry, and auditing security settings. The full README is longer than what was provided.
A documentation and configuration template for organizing multiple AI agents on one server, growing from a single agent to a coordinated specialist team.
Mainly Shell. The stack also includes Shell, Claude Code, VPS.
Setup difficulty is rated hard, with roughly 1h+ to a first successful run.
Mainly ops devops.
This repo across BitVibe Labs
Verify against the repo before relying on details.