You have data in your own API, a script, or a nightly job. Getting it into your analytics tool usually means a CSV export, a manual upload, or a custom integration someone has to maintain.
We just made that one command.
Databox CLI brings Databox into your terminal. If it prints JSON, you can pipe it straight into a Databox dataset. You get a clear result back every time: how many rows came in, what was added, what was updated, and what was rejected.
Create data sources, load data, build metrics, and automate workflows directly from your terminal. Use 90+ commands yourself, or let AI coding agents like Claude Code, Cursor, and Codex do the work with 10 ready-to-use agent skills.
Connect your AI Analyst to the tools your business runs on. It pulls context from your CRM or support desk, so every answer reflects what's happening in your business, and it can act on what it finds. Choose from 10+ connectors or add any MCP server.
It's the end of the month. Your client needs a performance report, so you open five tools, screenshot the numbers, paste them into Google Slides, and spend two hours making it look like you didn't just paste screenshots into Google Slides.
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.
Genie, our AI Analyst, can already tell you what changed in your numbers. It's never been able to tell you why, because the why almost never lives in Databox.
Revenue drops 8%, and the real reason is a stalled deal in HubSpot, a pricing objection buried in a Slack thread, or a support ticket nobody flagged. Right now, finding that out means leaving your dashboard, opening three other tools, and piecing it together yourself. Every time.
Next week, we're launching MCP Connectors. Connect your CRM, Slack, support desk, or any MCP server, and your AI Analyst gets that same context, right inside the conversation. Ask why a number moved, and it points to the actual deal or thread behind it, not just the number.
Turn any conversation with your AI Analyst into a polished report, slide deck, or interactive document built from your live data. Generate it from a single prompt, then share it via public link or download as a PDF.
Last week I asked here where you go to find out why a number moved. The answers were almost all the same: the CRM, Slack, the support desk, Linear, a doc somewhere. Anywhere except the dashboard.
That's what we launched today.
With MCP Connectors, you connect the tools your team already uses, and Genie, our AI Analyst, uses them to answer your questions. Ask why signups dropped 18%, and it checks Linear, finds the signup form that shipped Tuesday and breaks on Safari, and ties it to the drop. You get the number and the reason in one answer.
Give your AI Analyst a prompt and a schedule. It analyzes your live data, prepares the report or analysis you asked for, and delivers it by email, Slack, or in-app. The recurring work you do by hand today gets done automatically.
