What happens when you give Claude access to 33 tools and 2.2M apps? We built it to find out. 🧩

Finding early traction and validating app ideas usually feels like a guessing game. Most makers rely on broad category trends or gut feelings, which is incredibly risky. The App Store Top Charts are a trap by the time an app is there, you're already too late to the trend.

We realized the key is analyzing micro-signals across millions of data points, but doing that manually takes forever.

So, alongside tracking 2.2 million apps, we just rolled out our MCP (Model Context Protocol) integration. You can now plug AppGazers directly into Claude, ChatGPT, Cursor or Windsurf.

Instead of manually digging through spreadsheets, you give your AI assistant access to 33 tools and 6 ready-made prompts covering our entire catalog, including ad creatives, keyword difficulty, and review analytics.

You can literally just ask your AI:

"Find Health & Fitness apps under 500K downloads a month that are gaining ratings fastest, and tell me what they charge."

Or:

"Read the negative reviews for this app and give me the five complaints worth fixing."

It gives independent developers the exact market intelligence large studios use, right inside their IDE or chat window.

We are gearing up for our Product Hunt launch soon and would love to hear from this community:

How are you currently using AI for market research, and what is the biggest data limitation you face right now?

Let me know your thoughts below!