Scrape Google Gemini into structured data.
Gemini answers questions in prose, folds sources behind a citation chip, and names brands inline — none of it in a shape you can query. cloro sends your prompt to Gemini and returns the answer, its cited sources, and every brand and entity it mentions as clean JSON or Markdown.
Gemini was built to be read, not queried.
The answer changes with every load. Citations sit behind a chip you have to expand. Brands are buried in sentences, not a list. And Gemini renders in a logged-in, JavaScript-heavy surface that resists automation. cloro handles the session, the rendering and the parsing, and hands you a record you can store and diff.
- Live answers rendered in a real browser session, not a stale cache
- Citation chips expanded and resolved to title, domain and URL
- Brands and entities extracted from prose, typed and deduplicated
- The same schema you get from every other engine cloro covers
One request, one record
Send a prompt and a locale. Get back a typed object you can index, alert on, or feed straight into an LLM.
Four layers of the answer, all typed
Everything Gemini shows a user, restructured into fields your code can rely on.
The answer text
The full synthesized response, stripped of navigation and interface chrome. Take it as plain text, or as Markdown with headings and lists preserved for grounding a model.
Cited sources
The pages Gemini grounds its answer on — resolved from citation chips into an ordered list of title, domain and URL, so you can see exactly who earned the reference.
Brands & products
Vendors and products named in the prose, extracted into a list with the order they appear — the raw material for answer-engine share of voice.
Entities, typed
People, organizations, places and products, labelled and deduplicated, so you can map what Gemini associates with a topic.
Locale-aware prompts
Ask as a user in a given country and language would. The answer, and the sources behind it, shift with the market you target.
One shared schema
The same field names you get from ChatGPT, Perplexity and AI Overview — so a cross-engine comparison is a group-by, not a rewrite.
# ask Gemini, get a structured record back curl https://api.cloro.cloud/v1/gemini \ -H "Authorization: Bearer $CLORO_KEY" \ -d '{ "prompt": "best crm for a small agency", "country": "us", "format": "json" }' # → response { "engine": "gemini", "prompt": "best crm for a small agency", "answer": "For a small agency, the strongest options...", "citations": [ { "rank": 1, "title": "CRM buyer's guide", "domain": "g2.com" }, { "rank": 2, "title": "Agency CRM comparison", "domain": "forbes.com" } ], "brands": ["HubSpot", "Pipedrive", "Zoho"], "entities": [ { "type": "organization", "name": "HubSpot" } ], "country": "us", "latency_ms": 3180 }
JSON to power apps. Markdown to feed models.
Ask for the shape that fits the job. Structured JSON for dashboards, rank stores and alerts. Clean Markdown when you're grounding an LLM on what Gemini actually said, headings and citation list intact.
- Stable field names, so day-over-day diffs are trivial
- Citations resolved to title, domain and URL
- Brands and entities extracted from the prose
- Country- and language-aware prompts
From prompt to stored record
You make one call. cloro absorbs everything that makes Gemini awkward to automate, and returns a record that's ready to index.
You send a prompt
A prompt, a country and language, and your output format. That's the whole request — no session or proxy to manage.
We render Gemini live
The prompt runs in a real, logged-in browser session with rotation and retries handled upstream, so you get the live answer.
We parse the answer
Citation chips are expanded and resolved; brands and entities are extracted from the prose and typed into the shared schema.
You store & diff
A clean JSON or Markdown record lands in your pipeline, ready to index, alert on, or compare against last week's pull.
Who Gemini recommends
Run a prompt set on a schedule and track which brands Gemini names, and how often — your share of the answer, illustrative shape shown.
Turn Gemini answers into a scoreboard
- GEO & SEO teams — prove whether your work moves you up in Gemini's answers
- Brand & PR — watch how Gemini describes you, and which sources it cites instead
- Product & data — ground LLM features on fresh, structured Gemini output
- Agencies — report Gemini visibility across a client roster from one key
Good to know
What exactly does cloro extract from a Gemini answer?
Four layers: the synthesized answer text, the sources Gemini cites (title, domain and URL, in order), the brands and products named in the prose, and the entities it references — people, organizations and places — typed and deduplicated. It all returns in one record.
Do I need a Google account or my own proxies?
No. The session, rendering, rotation and retries all happen on our side. You authenticate with one cloro API key and receive parsed results.
Can I get the answer as Markdown instead of JSON?
Yes. Pass "format": "markdown" to receive the answer with headings, lists and a citation list preserved — ideal for grounding a model or building a knowledge base. JSON is best for dashboards, rank stores and alerts.
Can I target a specific country or language?
Yes. Prompts are locale-aware, so you can capture the answer — and the sources behind it — that a user in a given market and language would actually see.
How is Gemini scraping billed?
Per successful call. If a request fails or returns nothing, it isn't billed, and your live usage counter reflects exactly what you've consumed.
Does the Gemini schema match the other engines?
Yes. Gemini returns the same field names as ChatGPT, Perplexity, Copilot, Grok and Google AI Overview, so comparing visibility across engines is a group-by rather than a rewrite.
Read Google Gemini like a database.
Spin up a key, send your first prompt in minutes, and start turning Gemini's answers into data you can track over time.