Databox MCP

Databox: AI-powered analytics for teams that need answers now. | Product Hunt

AI-powered analytics for teams that need answers now.

4.5•2 reviews•

900 followers

AI-powered analytics for teams that need answers now.

4.5•2 reviews•

900 followers

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Business intelligence software

Databox is an AI-powered business intelligence and analytics platform for teams that need clear, trusted answers fast. It offers the best of BI, without the complicated setup, steep price, or long learning curve. It provides a blend of powerful, but easy-to-use, features, from preparing datasets and creating the custom metrics your company needs to track, to building beautiful dashboards, customizing your reporting, and receiving AI-powered insights.

Overview

Launches6

Reviews2

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This is the 6th launch from Databox. View more

Databox MCP

Launching today

Chat with your business data inside Claude, ChatGPT and more

Databox MCP connects your business data to Claude, ChatGPT, Cursor, and n8n. Ask about revenue, campaigns, or pipeline in plain language and get answers grounded in your real metrics and business context.

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Launch tags:Productivity•Analytics•Artificial Intelligence

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Previous Databox Launches

Custom Integrations by DataboxBring missing data into Databox without writing code

Launched on May 6th, 2026

Genie by DataboxYour AI analyst for business performance

Launched on March 18th, 2026

Metrics Library by DataboxThe easiest way to make sense of your data.

Launched on February 1st, 2018

Goals by DataboxSet numeric goals and track your progress automatically.

Launched on December 1st, 2016

View all Databox launches

Forum Threads

p/databox•

9m ago

We just launched Databox MCP - and it's live on the leaderboard today.

https://www.producthunt.com/prod...

Most analytics tools give you a dashboard. You open it, look at it, and go back to your spreadsheet to answer the actual question.

We just changed that.

Databox MCP connects your business data to the AI tools you already use - Claude, ChatGPT, Cursor, n8n. Instead of building dashboards to get answers, you just ask. What happened to your CAC last week? Which campaign drove the most revenue? Your AI does the math using your real metrics, definitions, and historical context - and gives you an answer you can act on.

p/databox•

11d ago

How many steps does it take to answer a simple data question?

We've been thinking a lot about this moment. A stakeholder asks "how did our paid campaigns do last week?" or "are we on track for the month?" - and even with dashboards already built, getting a clean answer still takes more steps than it should.

You open the right tool. Filter the right date range. Cross-reference another source. Paste it into a Slack message. Sometimes you just end up saying "let me get back to you on that."

The data exists. The dashboards exist. But the path from question to answer still has too much friction in it.

That's the problem we set out to solve with Databox MCP - launching on Product Hunt May 28. Instead of navigating dashboards, you ask the question directly in whatever AI tool you already use - Claude, ChatGPT, n8n, Cursor - and get an answer pulled from your live data.

p/databox•

9d ago

AI chat exports don’t keep the filters from inline charts

Noticed a small friction with the new AI + inline charts feature.

Steps:

1. Ask the AI to show "MRR last 30 days" with a filter for Plan = Pro

1. The inline chart displays correctly

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4.5

Based on 2 reviews

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We built Databox MCP because of a pattern we kept seeing: teams were doing their thinking in Claude and ChatGPT, but their actual performance data lived elsewhere. So they'd export it, paste it in, and hope the AI understood it. It didn't. The data was already in Databox, connected, defined, with all the historical context. It just wasn't reachable from the tools where people were actually working. MCP closes that gap. One connection, and your AI can talk about your real numbers instead of guessing.

This is the part that matters more than people realize. An AI is only as good as the data layer underneath it. Databox isn't a pile of raw exports; it's a governed semantic layer: metrics defined once and consistently, data cleaned and modeled across all your sources, with the historical context that tells you whether a number is actually good or bad. That's the difference between an answer you can act on and a confident guess you have to double-check.

Asking questions and getting trusted answers is the obvious first use. What I'm most excited about is what comes next: workflows that act on the data on their own. Performance management, monitoring, and decisions that trigger automatically. Your AI stops being something you ask and starts being something that keeps the business moving week to week.

Proud of the team for shipping it.

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12m ago

Hi Product Hunt! 👋

I'm Pete from the Databox team, and today we're excited to share something we've been building for a while: Databox MCP.

Every team we talk to uses AI for writing, planning, and thinking through problems. When it comes to performance data, teams are still piecing it together by hand. Someone asks "why did my ad cost spike last week?" and answering takes 20 minutes of combing through multiple dashboards, adjusting date ranges and filters.

Some teams have shortcut this by uploading a CSV to Claude. The answer sounds confident, but it’s built on context that the AI doesn’t have. No metric definitions. No historical trends. No understanding of how their business measures success. The answers are hard to trust, and even harder to act on.

Databox MCP closes that gap.

Databox connects to all of your tools, then it feeds the AI tools with data, analysis and insights. You ask questions in plain language, and the answers come grounded in your real business data: your metric definitions, your historical context, and the way your team measures success.

Here are a few things you can do with it:

Get fast answers without leaving your AI tools: Ask "why did ad cost spike last week?" and your AI pulls the answer from your trusted data, and gives you a written explanation with visual context.

Point your AI at any of your dashboards:   Say "analyze my Google Ads dashboard" or "summarize my client reporting dashboard," and your AI knows which metrics to pull. You skip the setup work that usually goes into every AI prompt.

Push new data into Databox from your AI: Upload a CSV or pull from an API in your AI conversation, and your AI sends it to Databox as a clean, structured dataset. Analyze it the same minute alongside the metrics you already track.

Rely on Databox for mathematical analysis: Whether it's simple things like understanding wether an increase in a number is good or bad, or more complicated things like calculating correlations or detecting anomalies, Databox is doing the math the same every time.

Turn recurring work into workflows: Connect MCP to n8n or Make, and your recurring AI analysis runs on its own. Schedule the Monday performance summary, trigger alerts when key metrics change, and send executive summaries that arrive with the context built in.

We soft-launched it in February, and the most interesting thing has been watching what customers do with it. Rick Kranz used the Databox MCP with Claude to turn traffic, search, and CRM data into weekly content creation recommendations. He even made the skill available for others to download. Agency operations leaders like Gary Magnone started using it to spot the root cause of KPI spikes in minutes instead of hours. High volume digital advertising agency owners like (like Kamil Rextin) used it to build paid media benchmarks from client data. Island, a software development firm used it to automate data analysis for 25 leading online publications, cutting reporting time by 96%!

It takes 60 seconds to connect and is available on all paid Databox plans.

We'd love your input 👇

What's the one performance question your team asks every week - but still takes too long to answer?

Thanks for checking it out 🙏

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6d ago

Sounds very interesting.

I actually do upload a google sheet of my company stats which includes revenue and marketing data. I have a Claude Project that analyzes the google sheet and then creates a dashboard. This solution is very interesting and more dynamic.

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38m ago

•21 reviews

Databox serves as a crucial asset for businesses that rely on data. It simplifies the process of monitoring, analyzing, & displaying insights from various sources in real-time with its #ufi streamline.

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254 views3yr ago

Emailee

•4 reviews

Amazing dashboard tool, professional, sleek, so easy to setup compared to looker studio

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240 views2yr ago