Documentation
How to run obop, build on it and connect AI agents to it. Everything here was checked against the code and, where there is a command, run.
obop is an open-source business platform. One program serves the web app, a REST API, an MCP server and a command line from the same definitions, on one data model.
Where to start
- New to obop? Read Getting started. It covers the hosted beta, self-hosting with Docker and PostgreSQL, and local development with SQLite.
- Want an AI agent to work with obop? Start with Agents, then create an agent token and connect over MCP.
- Building your own app? The module manifest reference explains how to describe models, fields, workflows and permissions in one
obop.tomlfile. - Looking something up? See the CLI, REST API, environment variables and the FAQ.
How the documentation is organised
| Section | What it answers |
|---|---|
| Start here | How do I get an instance and use it? |
| Concepts | What are apps, data classes, permission groups, workflows and instances? |
| Agents | How do I set agents up safely, and what can they do? |
| Reference | Exact commands, endpoints, settings and limits. |
Status
obop is in beta. Where a feature is not built yet, the page says so plainly. The roadmap lists what exists and what does not, and the changelog lists what changed.
Every page here is also available as plain Markdown: add .md instead of the trailing slash, or read the whole documentation in one file at llms-full.txt.