The initial use case that spurred this project was business analytics, specifically generating product usage dashboards.
This project's main inspiration is Marimo, an open source python notebook that can be "queried with SQL, run as a script, and deployed as an app" [1]. The recent release of Marimo Pair [2] demonstrated the power of connecting AI agents like Claude Code to Marimo notebooks directly. This project seeks to build on that work by incorporating a LangGraph agent with two key abilities: (1) the ability to execute queries against a connected data warehouse (such as Snowflake); (2) the ability to write Marimo notebooks.
When prompted, the LangGraph agent will run exploratory data analysis using database query tools. Then, it creates a polished Marimo notebook that's presented to the user in read-only mode. This project intentionally hides the Marimo edit mode. That means that the end user only ever sees a finished, read-only data app. Ease of use and trust in AI output were the main drivers behind this decision.
4 data sources are currently supported: Snowflake, BigQuery, Postgres, and Metabase. The code for the database query tools was derived from Google's open source MCP Toolbox for Databases.
There is currently no support for MCP. Instead, data query tools are hardcoded. This decision was made to ensure high quality AI queries and limit tool bloat.
This is an early stage project, and is configured to only run locally at this time.
[1] https://github.com/marimo-team/marimo [2] https://news.ycombinator.com/item?id=47678844