Run your own instance

Studiograph runs as a single server process. One process serves the web app, the API, the built-in agent, and sync for one workspace. There is nothing else to operate — no separate database server or frontend deployment.

What you need

Node.js 22.19 or later — or Docker, which bundles it.
A model provider API key for the agent: Anthropic, OpenAI, Google, xAI, Groq, or OpenRouter. You can set it during first boot or later in the web app under Settings.
Optionally, Cloudflare R2 for uploaded file storage. By default files are stored on the server’s disk — see Storage & backups.

Three ways to run it

Method	Best for	Setup
Bare `studiograph serve`	Any machine you control — a laptop, a VPS, a home server	Install the npm package, init, serve
Docker	A host with Docker; reproducible setup with a single volume	`docker compose up -d`
Railway	Managed hosting with one command	`studiograph deploy railway`

Quickstart: bare serve

npm install -g @studiograph/server
studiograph init "My Studio"
cd my-studio
studiograph serve

init creates a workspace directory: a git repository at the root plus a .studiograph/ config directory, with a baseline commit. serve starts the server on port 8000 (host 0.0.0.0) — run it from the workspace directory. On first boot it prompts for your AI provider and model, and the first browser visit creates the owner account. Use --port/--host (or the PORT/HOST env vars) to change the bind address. If the port is taken, the server auto-increments to the next free one. It opens your browser automatically unless STUDIOGRAPH_NO_OPEN=1 is set.

Next steps

Docker

Run the server in a container with a single persistent volume.

Railway

Provision and deploy a managed instance with one command.

Configuration

Environment variables and where settings live.

Storage & backups

What to back up, and the one-command backup bundle.

​What you need

​Three ways to run it

​Quickstart: bare serve

​Next steps