### Run the demo
```bash
uvx sqldash init --demo
uvx sqldash serve
```
`init --demo` creates a `.sqldash/` folder with a sample dashboard, a `metrics.yaml`, an
`agents.yaml`, and a generated orders CSV. `serve` opens the dashboard in your browser.
> [!TIP]
> The demo runs on DuckDB over the local CSV, so there is no warehouse to connect, no
> credentials, and nothing to set up.
### Change something
Open `.sqldash/demo.yaml` in your editor, change a tile's `chart: bar` to `chart: pie`,
and save. The dashboard updates in place.
You can make the same kind of change from the browser. Click **Edit** to drag, resize,
or delete tiles, or **+ Explore** to write a query, chart it, and add it as a new tile,
and sqldash writes each change back to the file. For changes you would rather describe
than click, open [AI Studio](/docs/studio/) and ask your coding agent.
### Connect your warehouse
Install sqldash with the driver for your warehouse, then run setup inside the project.
```bash
uv tool install 'sqldash[snowflake]'
sqldash setup
```
`setup` asks for the connection details, keeps your credentials out of the repo, and
tests the connection. [Setup](/docs/setup/) covers every flag, and
[Sources](/docs/sources/) covers every warehouse.
### Give your agent the metrics
Add sqldash as an MCP server in your coding agent, from inside the project.
```bash title="Codex"
codex mcp add sqldash -- sqldash mcp "$PWD"
```
```bash title="Claude Code"
claude mcp add sqldash -- sqldash mcp "$PWD"
```
Now your agent can answer questions from the same governed metrics your dashboards use.
> [!NOTE]
> These commands use the sqldash you installed with your warehouse driver, so the MCP
> server has the driver too. `"$PWD"` saves the project's absolute path, which matters
> because Codex keeps the setting for every project. If you are still on the demo and
> never installed sqldash, use `uvx sqldash mcp "$PWD"` instead.