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I built a Chrome extension that shows what AI agents actually see on your site — and it made me rethink GA4 completely

I've been running an API-first site for a few months (AgentShare — DeFi data for AI agents).

GA4 shows almost nothing. But my server logs tell a completely different story: GPTBot, ClaudeBot, dozens of MCP clients — they're calling my API every single day.

GA4 is blind to AI agents. They don't load JavaScript, they don't click buttons, they don't fire analytics events. They just read JSON and call endpoints.

So I built a Chrome extension that shows what AI agents actually see when they visit any website:

Agent Readiness Score (0–100) — based on robots.txt, llms.txt, ai.txt, and MCP discovery

AI crawler policy table — shows what bots like GPTBot, ClaudeBot, and PerplexityBot are allowed to do

Prompt injection scanner — detects hidden text and invisible elements that might hijack AI agents (new in v0.5)

MCP Connect — copy-paste config for Cursor, Claude Desktop, VS Code, Windsurf

The extension runs entirely client-side. No content is uploaded to any server.

What I learned: a low score doesn't mean your site is "bad." It means AI agents might be ignoring your content because the structure isn't machine-friendly. If that matters to you, this might help.

Link: https://chromewebstore.google.com/detail/nimndnhajfkicbnipbfdkmgencjejjed

Would love feedback from other API-first builders:

What metrics do you think matter most for AI visibility?

How are you tracking traffic that GA4 can't see?

Building in public, one awkward step at a time. 🚀

on July 28, 2026
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    The shift from tracking human visitors to understanding machine visitors is going to become a bigger problem for many websites.

    Interesting that you’re focusing on visibility and structure rather than just traffic numbers. Curious how you’re thinking about measuring “AI visibility” as these agent behaviors keep changing.

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      Thanks for the great feedback! You hit the nail on the head regarding the shift to machine visitors.

      Right now, I'm defining "AI Visibility" by two core metrics:

      Information Accessibility Score: How clean and structured the DOM appears to an agent once UI clutter, popups, and dynamic scripts are stripped away.

      Core Data Extractability: Whether an agent can correctly parse key entities (like pricing, CTA, or value props) without hallucinating or losing context.

      Since agent behaviors evolve rapidly, the extension currently acts as an instant "X-ray" for what LLM crawlers parse. Next, I'm working on a dynamic scoring system that benchmarks a site against how top models (Claude, GPT, Perplexity) actually digest it.

      Are you currently working on something related, or noticing AI crawlers affecting your own projects?

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        That’s an interesting way to frame it. I’m seeing some of the same questions around how AI systems interpret sites, especially as the behavior keeps changing. Happy to continue the conversation beyond the thread — what’s the best email to reach you at?

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          Thanks Aryan! I'd love to connect and chat further. You can reach me at admin@agentshare.dev ! Looking forward to exchanging insights!

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            Thanks! I’ve just sent it over.

            Looking forward to hearing your thoughts whenever you have a chance.