Visiblee AI is a generative engine optimisation (GEO) platform that shows how AI describes your brand. It tracks mentions and citations across ChatGPT, Claude, Perplexity, Gemini and Google AI Overviews by model, region and customer segment, with competitor benchmarks and cited-source analysis turned into concrete recommendations. For developers: a REST API to pull every metric into your own stack, an MCP server so your AI agents can query it directly, and a CLI for scripting reports.


Hey everyone 👋 Baz here, maker of Visiblee AI. I built this after realising that when people ask ChatGPT or Perplexity for "the best X", a handful of brands get named and everyone else is invisible — and almost nobody can tell you which side of that line they're on. Visiblee AI runs your buyers' real questions across the major AI models on a schedule and shows you what comes back: whether you're mentioned, how you're described, which competitors get named instead, and which sources the models are pulling from. Then it gives you concrete steps to improve your visibility. It's built to be hands-on-keyboard friendly too — full REST API, an MCP server so your own AI agents can query your data, and a CLI for scripting reports. Plans start at $24/month with a 7-day free trial on everything. Would genuinely love feedback — especially on what you'd want to see in the reports. Happy to answer anything! 🙌
The MCP integration is what stands out to me — most GEO/visibility tools just hand you a dashboard, but wiring Visiblee straight into Claude or ChatGPT so an agent can pull the weekly score and flag gaps on its own is a much more useful shape for this kind of data. One methodology question: for "mention rate" and "citations," are you running live prompts against each model's actual API on a schedule, or inferring visibility some other way? That distinction matters a lot for how much I'd trust the trend lines, since model behavior shifts between versions and providers don't always expose the same signals.
This is actually kind of wild once you think about it, brands are already fighting for SEO rankings and now there's a whole second battle just to get mentioned when someone asks ChatGPT or Perplexity for a recommendation. The per-model and per-region breakdown is smart since I'd imagine visibility isn't even close to the same across providers. MCP server + CLI is a nice touch for anyone who wants this piped straight into their own stack instead of staring at a dashboard. Curious how "citations" gets tracked though, like is it pulling live from each model's API on a schedule or is there some inference happening? That would change a lot about how much I'd trust the trend line.




Hey everyone 👋 Baz here, maker of Visiblee AI. I built this after realising that when people ask ChatGPT or Perplexity for "the best X", a handful of brands get named and everyone else is invisible — and almost nobody can tell you which side of that line they're on. Visiblee AI runs your buyers' real questions across the major AI models on a schedule and shows you what comes back: whether you're mentioned, how you're described, which competitors get named instead, and which sources the models are pulling from. Then it gives you concrete steps to improve your visibility. It's built to be hands-on-keyboard friendly too — full REST API, an MCP server so your own AI agents can query your data, and a CLI for scripting reports. Plans start at $24/month with a 7-day free trial on everything. Would genuinely love feedback — especially on what you'd want to see in the reports. Happy to answer anything! 🙌
The MCP integration is what stands out to me — most GEO/visibility tools just hand you a dashboard, but wiring Visiblee straight into Claude or ChatGPT so an agent can pull the weekly score and flag gaps on its own is a much more useful shape for this kind of data. One methodology question: for "mention rate" and "citations," are you running live prompts against each model's actual API on a schedule, or inferring visibility some other way? That distinction matters a lot for how much I'd trust the trend lines, since model behavior shifts between versions and providers don't always expose the same signals.
This is actually kind of wild once you think about it, brands are already fighting for SEO rankings and now there's a whole second battle just to get mentioned when someone asks ChatGPT or Perplexity for a recommendation. The per-model and per-region breakdown is smart since I'd imagine visibility isn't even close to the same across providers. MCP server + CLI is a nice touch for anyone who wants this piped straight into their own stack instead of staring at a dashboard. Curious how "citations" gets tracked though, like is it pulling live from each model's API on a schedule or is there some inference happening? That would change a lot about how much I'd trust the trend line.
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