Home/Models/Gemini
POST /v1/monitor/gemini

Gemini Scraper API

What the Gemini app actually tells your customers.

Gemini ships on Android, in Chrome and in Google Workspace — its answers reach a massive audience that never opens ChatGPT. The Gemini app's responses differ from the Gemini developer API: different grounding, different search behaviour, different voice. llmdata captures the real consumer Gemini experience and returns it as structured JSON.

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Example request
curl -X POST https://api.llmdata.dev/v1/monitor/gemini \
  -H "Authorization: Bearer $LLMDATA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "best accounting software for freelancers",
    "country": "GB"
  }'
Response
{
  "success": true,
  "result": {
    "text": "For freelancers, the standout options are...",
    "sources": [
      { "title": "...", "url": "https://..." }
    ],
    "entities": ["FreeAgent", "QuickBooks", "Xero"]
  }
}

What you get in every response

text / markdown

The complete Gemini answer.

sources

Grounding links when Gemini cites the web.

entities

Brands and products mentioned in the response.

What teams build with the Gemini endpoint

Android-audience visibility

Gemini is the default assistant for a huge Android user base — know what it recommends in your category.

Cross-model comparison

Run the same prompt through Gemini, ChatGPT and Perplexity and diff which brands each one favours.

Market-specific tracking

Gemini's answers vary by country — monitor each market you sell in.

Gemini scraping FAQ

Is this the Gemini API from Google AI Studio?

No — that's a developer model endpoint. llmdata captures the consumer Gemini app experience, which uses different grounding and produces different answers than raw API calls.

Does it include Gemini's web sources?

Yes, when Gemini grounds an answer in search results we return those links in the sources array.

Can I track my brand daily?

Yes — schedule your prompt set daily or hourly and diff the entities array to catch changes.

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