Most data work isn t analysis. It s setup and upkeep.
Creating a data source for a new client. Pushing rows from an internal tool. Building the same custom metric for the fifth account in a row. Checking why last night s ingestion failed. Updating permissions when someone leaves the team.
All of it lives behind clicks. So it doesn t run in CI, it doesn t run on a schedule, and your AI agent can t touch it.
That s why we built Databox CLI - launching on Product Hunt on November 6. It puts the Databox API in your terminal: data sources, datasets, data ingestion, custom metrics, databoards, users and client accounts. One install, JSON or CSV output, clear exit codes for scripts. It also ships with agent skills, so Claude Code (or any agent that runs shell commands) can manage your Databox setup for you.
Thanks for the detailed review, Ulykbek. Glad the MCP server is helping you query live data straight from your dev environment, that's exactly the workflow we built it for.
On the JSON formatting friction: fair feedback, unconventional payloads shouldn't need manual cleanup before ingestion. We're looking at ways to handle that more natively.
On refresh intervals: sync frequency does scale with plan tier, and some of that comes down to rate limits on the data provider's side, not just us. That said, we hear you on real-time verification during testing, and it's worth us looking at how sandboxed/dev setups are handled specifically.
Thanks again for the detailed feedback, it helps us prioritize the right things.