We tested AMZScout MCP across 50 niches - here's what actually surprised us

When we first shipped the MCP integration, we assumed the main value would be speed — the agent pulls the data itself, no more copy-pasting between tabs.

But the more interesting part turned out to be something else.

Once an AI agent has access to real data (sales volume, pricing, competition, reviews), it stops "guessing" and starts asking sharper follow-up questions. Instead of "this niche looks promising," it says something like: "average rating across the top 10 is 4.1, 6 of 10 have under 500 reviews, but entry cost (ads + inventory) is above category average - worth offsetting that with a positioning angle?"

So the agent stops being a "confident text generator" and starts acting more like a sparring partner that actually pushes back based on numbers, not vibes.

A couple of questions for the community:

• Has anyone here built a workflow where the AI agent makes the actual go/no-go call, and a human just signs off?

• What metrics would you want an agent to always check before it's allowed to give a recommendation?

Sharing this because we're genuinely curious where AI agents still hallucinate in e-commerce analysis, and where they're already reliable enough to trust.