🔎 Google AI Overview API

The Google AI Overview API sends any search query to Google's AI Overview and returns the AI-generated answer (its text blocks) plus the cited source links, as structured JSON. When Google defers generation, this API resolves the answer for you automatically. MCP-ready so Claude and other AI agents can call it as a tool.

Example code (Python): https://github.com/johnisanerd/Apify-Google-AI-Overview-API

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📋 What this API returns

Field	Description
query	The search query this row answers.
ai_overview_present	true if Google showed an AI Overview, false if none was available.
text_blocks	The AI Overview content as ordered blocks: paragraphs, headings, lists, and tables.
references	The cited sources behind the overview, each with title, link, snippet, and source.
used_dedicated_api	true when Google deferred generation and a follow-up fetch was needed to resolve the answer.
retrievals_used	1 for an inline answer, 2 when a follow-up fetch was required.
thumbnail, header_images	Imagery shown with the overview, when present.
gl, hl, location	The country, language, and location used for the search.
note	A short explanation when no overview was returned.

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🎯 Use cases

• GEO / AEO monitoring. Track whether your brand or domain is cited in Google's AI Overview for the queries you care about.
• SEO research. See which sources Google's AI cites for a topic, and how the answer is phrased.
• Content strategy. Compare AI Overview answers across queries, countries, or over time.
• AI agent workflows. Drive this API over MCP from Claude (see below) to pull AI Overview answers in-conversation.
• Datasets for analysis. Batch hundreds of queries into one run and export the answers and citations as JSON.

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🔌 Integrations: Automate Google AI Overview API Monitoring

A single run answers one question ("is my brand cited for this query today?"). The real value comes from running the Google AI Overview API on a schedule, so you accumulate a history of how the overview and its cited sources shift over time. See the full list of Apify platform integrations.

Tasks and Schedules (the core recipe). Save one task per query set you watch (a brand list, a keyword list, or one country), then attach a schedule from the Actor's Actions, then Schedule menu. Useful cron strings: 0 7 * * * (daily at 7 AM), 0 */6 * * * (every 6 hours), 0 9 * * 1 (Mondays). One schedule can trigger many tasks at once. The Check if your brand appears in Google AI Overviews task is a ready-made starting point.

n8n. This API ships an n8n community node (see the n8n integration section below). A four-step monitor: Schedule Trigger, then the Google AI Overview API node, then a Filter on ai_overview_present, then Slack or email when your domain is missing from references.

Make and Zapier. The same pattern works no-code with Make and Zapier: trigger on a schedule, run the Actor, route the rows to where you need them.

Store the history (Supabase). Send each run's rows into a table so an AI Overview history builds up. No-code: the n8n Actor node, then a Supabase node. Or in Python (each row carries query, ai_overview_present, text_blocks, references, gl, hl):

from apify_client import ApifyClient
from supabase import create_client

apify = ApifyClient("YOUR_APIFY_TOKEN")
supabase = create_client("YOUR_SUPABASE_URL", "YOUR_SUPABASE_KEY")

run = apify.actor("johnvc/google-ai-overview-api").call(run_input={
    "queries": ["best crm for startups", "what is retrieval augmented generation"],
    "gl": "us",
    "hl": "en",
})
rows = list(apify.dataset(run["defaultDatasetId"]).iterate_items())
supabase.table("ai_overviews").upsert(rows).execute()

MCP and AI agents. Add this API as a tool in Claude or Cursor through the Apify MCP server so an agent can pull AI Overview answers inside AI agent workflows (see the Use this API from Claude section below).

Webhooks. For anything custom, fire an Apify webhook on ACTOR.RUN.SUCCEEDED to push each run's dataset into your own service.

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⚙️ Input examples

Single query

{
  "query": "what is the Siliconimist podcast?"
}

Many queries at once

{
  "queries": [
    "best practices for prompt engineering",
    "how does vector search work",
    "what is a transformer model"
  ]
}

Country and language targeting

{
  "query": "electric vehicle tax credit",
  "gl": "us",
  "hl": "en",
  "location": "Austin, Texas, United States"
}

Provide a single query, a list of queries, or both. At least one is required. The API returns one row per query.

Note: Google's AI Overview is currently shown for English searches (hl=en) in a limited set of countries. For some queries Google declines to show an overview at all; those rows come back with ai_overview_present: false and a short note.

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Sample output

One row per query. An AI Overview row (result_type: "ai_overview"), trimmed:

{
  "result_type": "ai_overview",
  "query": "what is retrieval augmented generation",
  "ai_overview_present": true,
  "text_blocks": [
    {"type": "paragraph", "text": "Retrieval augmented generation (RAG) pairs a language model with a search step that pulls in relevant documents before the model answers."},
    {"type": "list", "items": ["Retrieve relevant context", "Augment the prompt", "Generate the answer"]}
  ],
  "references": [
    {"title": "What is RAG?", "link": "https://example.com/rag-explained", "snippet": "RAG grounds a model's answer in retrieved sources.", "source": "example.com"}
  ],
  "used_dedicated_api": false,
  "retrievals_used": 1,
  "gl": "us",
  "hl": "en",
  "location": null,
  "note": null
}

When Google shows no overview, the row comes back with ai_overview_present: false and a short note explaining why.

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💰 Pricing (pay-per-event)

Event	Price	When it fires
setup	$0.01	Once per Actor run, at startup.
overview-retrieval	$0.015	Per retrieval. One for a standard answer; two when Google defers generation and a follow-up fetch is required.

Examples:

• A query whose answer is returned inline costs $0.01 + $0.015 = $0.025.
• A query where Google defers generation costs $0.01 + 2 x $0.015 = $0.04.
• A batch of 10 inline answers costs $0.01 + 10 x $0.015 = $0.16.

You are billed per retrieval the API actually performs, so deferred queries (which require a second fetch) are the only ones that cost two retrievals.

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🔌 Use this API from Claude (MCP)

This Actor is MCP-server-compatible, so Claude Code (free trial), Claude (desktop and web), Cursor, and other MCP clients can call it as a tool through Apify's hosted MCP server.

Add it with this Actor-specific URL:

https://mcp.apify.com/?tools=actors,docs,johnvc/google-ai-overview-api

Setup walkthrough:

Apify MCP integration docs: https://docs.apify.com/platform/integrations/mcp

New to Claude Code or Claude Cowork? Start a free trial here: https://claude.ai/referral/uIlpa7nPLg

Then ask Claude:

"Use the Google AI Overview API to get the AI Overview for 'what is the Siliconimist podcast?', and list the cited sources."

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🚀 How to get started

1. Open the Actor and enter a query (or a list of queries).
2. Optionally set the country (gl), language (hl), and location.
3. Run it and read the results from the dataset (JSON, CSV, Excel, or API).

View on Apify Store

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🔗 Related Tools

Tracking AI answer engines beyond Google? These tools from the same catalog pair well with the Google AI Overview API for generative engine optimization (GEO) and answer engine optimization (AEO) monitoring:

• Naver AI Overview API: the same AEO monitoring for Naver, Korea's dominant search engine, when you track the Korean market.
• Brave AI Mode API: AI-generated answers and their sources from Brave Search, for privacy-focused search visibility.
• Bing Copilot API: Microsoft's Bing Copilot AI answers, to round out cross-engine answer-engine monitoring.
• Google News API: pull the coverage behind a topic to see which publishers feed the sources an AI Overview cites.

An alternative such as Google AI Overview Scraper exists, but it currently carries a 1-star average rating and a higher per-run start fee. This API is actively maintained, holds a 5-star rating, returns clean structured JSON, and resolves Google's deferred generation automatically.

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❓ FAQ

Why does a query come back with ai_overview_present: false?

Google does not show an AI Overview for every query. It is more likely for question-style, informational searches, and is currently limited to English searches in certain countries. When none is shown, the row includes a short note.

What is used_dedicated_api / why do some queries cost two retrievals?

Google sometimes returns the AI Overview immediately and sometimes defers it, returning only a short-lived token. When that happens, this API makes a second call to resolve the full answer. That second call is the second retrieval.

Can I pass a token directly?

No. The deferral token expires within about a minute, so it is resolved automatically inside a single run rather than exposed as an input.

Can I schedule the Google AI Overview API?

Yes. Any run can be automated on a schedule. Create a saved task with your queries, then attach a schedule from the Actor's Actions, then Schedule menu. Concrete cron strings: 0 7 * * * for daily at 7 AM, 0 */6 * * * for every six hours, and 0 9 * * 1 for Mondays. One schedule can trigger many tasks at once, so you can watch dozens of brand or keyword lists from a single timer. See the Integrations section above for the full monitoring recipe.

Should I use an API or a web scraper for Google AI Overviews?

Both, and this Actor is both. A plain web scraper of Google Search returns messy HTML and breaks when the layout changes, while this Actor gives you the clean, structured result of a purpose-built API: call it yourself, pay per retrieval, no quotas, and get the same JSON whether you send one query or hundreds. It also resolves Google's deferred (page-token) generation for you, which a naive scraper misses.

Can I integrate the Google AI Overview API with other apps?

Yes. It connects to almost any cloud service through Apify integrations: Make, Zapier, Slack, the n8n community node, and webhooks on ACTOR.RUN.SUCCEEDED for custom actions. See the Integrations section above for full recipes.

Can I use the Google AI Overview API programmatically?

Yes. The Apify API runs the Actor, schedules it, and fetches datasets, and the apify-client package exists for both Node.js and Python. See the Apify API tab for ready-made snippets.

Can I use the Google AI Overview API through an MCP server?

Yes. Add it as a tool in any MCP client (Claude, Cursor, and others) through the hosted Apify MCP server with the Actor-specific URL https://mcp.apify.com/?tools=actors,docs,johnvc/google-ai-overview-api. In Claude Code (free trial) or Claude Cowork (free trial) your agent can then answer questions like "is my domain cited in the Google AI Overview for these ten queries?" inside AI agent workflows. See the Apify MCP docs.

How can I monitor AI Overviews across other search engines?

Pair this API with related tools in the same catalog: the Naver AI Overview API for Korean AEO monitoring, the Brave AI Mode API for Brave Search answers, and the Bing Copilot API for Microsoft's answer engine. Together they cover generative engine optimization across the major AI answer engines.

What is a Google AI Overview?

A Google AI Overview is the AI-generated summary Google shows at the top of some search results, with links to the sources it drew from. It grew out of Google's Search Generative Experience. Background: Google Search and large language models. You can see one yourself on Google.

Can I use AI Overview data in AI agent workflows?

Yes. Because the Actor is MCP-ready and returns clean JSON, it drops straight into AI agent workflows: an agent can call it as a tool, read the text_blocks and references, and decide what to do next. This is how teams wire AI Overview checks into agentic monitoring and reporting pipelines.

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n8n integration

Available as an n8n community node, n8n-nodes-google-ai-overview-api. In n8n: Settings, Community Nodes, install n8n-nodes-google-ai-overview-api, then use it in any workflow (it also works as an AI Agent tool).

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Featured Tasks

Ready-to-run examples that show this API solving a specific problem. Each opens its own setup so you can run it on your account in one click.

• Check if your brand appears in Google AI Overviews - the full AI Overview answer and cited sources for any brand query.
• See which sites Google AI Overview cites for a keyword - every source the AI Overview cites for a keyword, with link and position.
• Monitor Google AI Overviews from Claude via MCP - AI Overview answers and citations inside Claude chat via MCP.

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Last Updated: 2026.07.14