Show HN: Tracecast – open-source generative data apps built on top of Marimo
A tool for generating interactive data apps and product usage dashboards via AI chat, building on Marimo and LangGraph. It prioritizes ease of use and trust in AI output by presenting only polished, read-only applications.
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A tool for generating interactive data apps and product usage dashboards via AI chat, building on Marimo and LangGraph. It prioritizes ease of use and trust in AI output by presenting only polished, read-only applications.
Tracecast addresses the demand for simplified data analytics and dashboard generation within enterprises. By leveraging AI agents to query data warehouses and generate interactive Marimo notebooks, it democratizes access to data insights for non-technical users. The focus on read-only output enhances trust and reduces complexity, critical factors for B2B adoption. This approach minimizes the need for specialized data engineering or BI teams for routine reporting, accelerating decision-making cycles. The support for major data sources like Snowflake and BigQuery positions it for immediate relevance in existing data stacks. This project highlights a trend towards AI-driven automation in data visualization, shifting from manual dashboard creation to prompt-based, on-demand data application generation.
Hi HN, I'm Malachy, the founder of Tracecast. This project lets you generate interactive data apps on top of your data, using a Cursor-style AI chat. It stitches together Marimo, LangGraph agents, and data warehouse query tools. It has an Apache 2.0 license.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
generative data apps
Cursor-style AI chat
Marimo
LangGraph agents
data warehouse query tools
Apache 2.0 license
business analytics
product usage dashboards
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What is Tracecast – open-source generative data apps built on top of Marimo?
Tracecast – open-source generative data apps built on top of Marimo is analyzed by our AI as: A tool for generating interactive data apps and product usage dashboards via AI chat, building on Marimo and LangGraph. It prioritizes ease of use and trust in AI output by presenting only polished, read-only applications.. It focuses on Tracecast addresses the demand for simplified data analytics and dashboard generation within enterprises. By leveraging AI agents to query data war...
Where did Tracecast – open-source generative data apps built on top of Marimo originate?
Data for Tracecast – open-source generative data apps built on top of Marimo was aggregated directly from the Hacker News community ecosystem, representing raw developer and early-adopter sentiment.
When was Tracecast – open-source generative data apps built on top of Marimo publicly launched?
The initial public indexing or launch date for Tracecast – open-source generative data apps built on top of Marimo within our tracked developer communities was recorded on May 19, 2026.
How popular is Tracecast – open-source generative data apps built on top of Marimo?
Tracecast – open-source generative data apps built on top of Marimo has achieved measurable traction, logging over 5 traction score and facilitating 0 recorded discussions or engagements.
Which technical categories define Tracecast – open-source generative data apps built on top of Marimo?
Based on metadata extraction, Tracecast – open-source generative data apps built on top of Marimo is categorized under topics such as: generative data apps, Cursor-style AI chat, Marimo, LangGraph agents.
How does the creator describe Tracecast – open-source generative data apps built on top of Marimo?
The original author or development team describes the product as follows: "Hi HN, I'm Malachy, the founder of Tracecast. This project lets you generate interactive data apps on top of your data, using a Cursor-style AI chat. It stitches together Marimo, LangGraph agents, ..."
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