Geass documentation
Geass turns servers you already own, from a single VPS to a rack of bare metal, into a managed cloud. You ship apps and databases from one dashboard, a command line or an AI agent, scale across machines, back up your data, and connect the clouds you already use, while everything runs on hardware you control.
These docs describe what Geass does today: what each feature is for, how to use it, what it does under the hood, and what to check when something goes wrong.
Start here
Section titled “Start here”
What is Geass
What it is, who it is for, and when it is the right tool.
Install Geass
One command on a fresh server. Requirements, what the installer does, how to confirm it worked.
Deploy your first app
From a fresh install to a running, reachable app.
Core concepts
Projects, environments, resources, pending changes, nodes and connections.
Connect your clouds
Section titled “Connect your clouds”Geass uses accounts you already have. Each one is a connector in Settings → Connectors. See Cloud connectors for the permissions each one needs.
AWS
S3 buckets and database backups in your own AWS account.
GitHub
Deploy on every push, with a preview environment for each pull request.
Cloudflare
DNS for the dashboard and an optional Cloudflare Tunnel.
PlanetScale
Managed MySQL and Postgres databases in your PlanetScale organization (experimental).
Build and deploy
Section titled “Build and deploy”
Apps
Run code from a Git repository or a container image.
GitHub and builds
Connect repositories and deploy on every push.
Pull-request environments
A throwaway copy of your project for every pull request.
Domains and TLS
Put your apps and the dashboard on your own domain.
Data and storage
Section titled “Data and storage”
Databases
Postgres, MySQL, Redis and SQLite, with the connect string wired into your apps.
Backups and restore
Back up to your own AWS account and restore to a new database.
Object storage
Buckets for your apps, in the cluster or in AWS.
Storage and volumes
Local storage, the Longhorn add-on, and resizing volumes.
Run and scale
Section titled “Run and scale”
Scaling and placement
Replicas, regions, and how workloads land on nodes.
Sleep when idle
Stop a service while nobody uses it and start it on the next request.
Compliance node tags
Keep a project's work on the servers you choose, and other projects off them.
Network isolation
Projects are private by default. Open exactly what you need.
Logs, metrics and terminal
See what your services are doing and get a shell in them.
Troubleshooting
Symptoms, causes and fixes, in the dashboard and with kubectl.
Automate
Section titled “Automate”
Command line
Install geass, sign in with a code you approve in the dashboard, then deploy, watch and scale from a terminal or CI.
MCP server for AI agents
Let an AI agent inspect and run services as an API token, limited by that token's role.
Users and API tokens
Dashboard roles, and tokens for scripts, CI, the command line and agents.
Reference
Section titled “Reference”
REST API
The versioned /api/v1 and the dashboard routes, with API tokens.
CLI commands
Every geass command, flag, environment variable and exit code.
MCP tools
Every tool the geass MCP server offers an agent.
Resources
Every custom resource, field by field.
Configuration
Installer variables, operator flags and platform settings.
Glossary
The words Geass uses, in one place.