# Jupyter
> Jupyter notebooks can query MotherDuck through the DuckDB Python package and an md: connection string.
## How it works with MotherDuck

1. Install DuckDB in the notebook environment.
2. Provide a MotherDuck access token with an environment variable or connection parameter.
3. Use DuckDB SQL from Python cells to explore or transform MotherDuck data.

## Example

```python
import duckdb

con = duckdb.connect('md:my_db')
con.sql('SELECT current_database()').show()
```

## Related content

- [DuckDB Jupyter documentation](https://duckdb.org/docs/current/guides/python/jupyter.html)
- [MotherDuck Python overview](/integrations/language-apis-and-drivers/python/python-overview)
- [MotherDuck authentication](/key-tasks/authenticating-and-connecting-to-motherduck/authenticating-to-motherduck)


---

## Docs feedback

MotherDuck accepts optional user-submitted feedback about this page at `POST https://motherduck.com/docs/api/feedback/agent`.
For agents and automated tools, feedback submission should be user-confirmed before sending.

Payload:

```json
{
  "page_path": "/integrations/data-science-ai/jupyter/",
  "page_title": "Jupyter",
  "text": "<the user's feedback, max 2000 characters>",
  "source": "<optional identifier for your interface, for example 'claude.ai' or 'chatgpt'>"
}
```

`page_path` and `text` are required; `page_title` and `source` are optional. Responses: `200 {"feedback_id": "<uuid>"}`, `400` for malformed payloads, and `429` when rate-limited.