Quick start

From zero to a running application backend in three commands — and to a hosted one in five. Everything the backend is lives in your project folder, so the loop is: scaffold the files, run them locally, publish the same files.

1. Install the CLI#

# version-pinned tarball, served from snoozestack.com (not the npm registry)
npm install -g --ignore-scripts https://snoozestack.com/cli/snoozestack-1.56.0.tgz

2. Scaffold and run locally#

init writes a snoozestack/ folder — project.toml (the complete, portable definition of the application), a starter function, and a schema.mjs. dev runs the whole runtime natively — functions, database, storage, queues, schedules, signals, sites — with no Docker and no account needed yet:

cd ~/code/my-app
snoozestack init
snoozestack dev
# → dashboard: http://localhost:8787/

The one link it prints is the local dashboard — the same console the hosted portal shows, over your local state. Edit a function and the next request runs the new code; edit project.toml or schema.mjs and it reloads in place. A committed seed.mjs, if you add one, gives every fresh checkout working data. Sign-in works locally too, on the same identity plane the hosted project runs, seeded with user@test.com / 1234 — see Authentication.

3. Create the hosted project and publish#

When you want it on the internet: sign in, create a project, link the folder to it, and publish. preview runs the files in your own temporary copy of the project, at its own URL; publish validates them, records them as an immutable release, and deploys it to production.

snoozestack user login
snoozestack projects create my-app
snoozestack link --project my-app          # records it in snoozestack/project.toml
 
snoozestack preview                        # optional: try it first
# preview-@you: ready
#   https://preview-<id>-my-app.snzzz.com
snoozestack publish
# Published "my-app" — release r1 is production.   → https://my-app.snzzz.com

4. Connect your AI client#

Open the project's Overview in the console and create an MCP access token. The token is shown once, with a setup prompt you can paste into Codex, Claude, or another AI client. For Claude Code, that prompt gives you:

claude mcp add --transport http snoozestack-my-app \
  https://snoozestack.com/api/mcp/my-app \
  --header "Authorization: Bearer sb_mcp_..."

Your assistant can now edit and validate the project files, publish, set secrets, and read signals — the same lifecycle you just ran by hand. These docs come down the same connection, so it follows the platform's patterns instead of guessing at them. MCP has the full tool catalogue and what a token can't reach.

5. Talk to it from your app#

Paste this into the AI client you connected in step 4. It has the project's management tools and documentation, so it can adapt the integration to the app that's actually in your folder.

Create a todos web app with authentication.