# Google AI Overview Scraper (`searchapi/google-ai-overview-scraper`) Actor

Scrapes Google AI Overviews (SGE) for any query. Extracts the overview text and HTML, model/provider, sources, inline references, follow-up/related questions, organic results, extraction confidence, and more.

- **URL**: https://apify.com/searchapi/google-ai-overview-scraper.md
- **Developed by:** [Search API](https://apify.com/searchapi) (community)
- **Categories:** AI, Developer tools, Automation
- **Stats:** 105 total users, 5 monthly users, 98.6% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.99 / 1,000 google ai overview scraper results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Google AI Overview Scraper

Scrapes Google AI Overviews (SGE) for any query. Extracts the overview text and HTML, model/provider, sources, inline references, follow-up/related questions, organic results, extraction confidence, and more.

### What this Actor collects

The Actor stores one clean JSON record per Google AI Overview, including overview text and HTML, provider, citations and inline references, follow-up questions, related organic results, confidence signals, locale, and retrieval provenance when available.

- Uses the input limits and filters below to control the crawl.
- Stores source-backed fields defined by the 44-field dataset schema.
- Omits optional fields when the source does not expose a value instead of writing nulls or fabricated placeholders.

### Use cases

- Answer-engine monitoring
- Citation and source research
- Generative-search analysis

### Input

Provide input in JSON. Fields marked required must be supplied. The Default / example column shows a schema default when one exists; otherwise it shows a documented prefill or fixture value.

| Field | Type | Required | Default / example | Description |
| --- | --- | :---: | --- | --- |
| `queries` | array | Yes | `["What is quantum computing"]` | List of search queries to scrape AI Overviews for. |
| `maxItems` | integer | No | `10` | Maximum number of results to return. |
| `gl` | string | No | `"us"` | Google country parameter (e.g. 'us', 'uk', 'in'). |
| `hl` | string | No | `"en"` | Google language parameter (e.g. 'en', 'es', 'fr'). |
| `proxyConfiguration` | object | No | `{"useApifyProxy":true,"apifyProxyGroups":["GOOGLE_SERP"]}` | Select proxies to use for the scraper. |

#### Example input

```json
{
  "queries": [
    "what is machine learning"
  ],
  "maxItems": 20,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "GOOGLE_SERP"
    ]
  },
  "gl": "us",
  "hl": "en"
}
```

### Output

The default dataset contains one item per query that yields an AI Overview. The following are the most useful fields; citations, follow-ups, organic results, and model details appear only when Google exposes them.

| Field | Type | Description |
| --- | --- | --- |
| `position` | integer | Query Position |
| `searchQuery` | string | Search Query |
| `summaryTitle` | string | Summary Title |
| `aiSummary` | string | AI Summary |
| `sourcesCount` | integer | Sources Count |
| `relatedQuestionsCount` | integer | Related Questions Count |
| `organicResultsCount` | integer | Organic Results Count |
| `extractionConfidence` | string | Extraction Confidence |
| `scrapedAt` | string | Scraped At |
| `type` | string | Record Type |
| `query` | string | Query |
| `resultType` | string | Result Type |
| `page` | integer | Page |
| `queryLength` | integer | Query Length |
| `queryWordCount` | integer | Query Word Count |
| `aiSummaryHtml` | string | Clean Summary HTML |

<details>
<summary>All 44 declared dataset fields</summary>

`type`, `resultType`, `position`, `page`, `query`, `searchQuery`, `queryLength`, `queryWordCount`, `aiSummary`, `aiSummaryHtml`
`aiSummaryLength`, `aiSummaryTokens`, `model`, `modelProvider`, `summarySections`, `summarySectionsCount`, `sources`, `sourcesCount`, `sourceUrls`, `sourceDomains`
`inlineReferences`, `inlineReferencesCount`, `followupQuestions`, `followupQuestionsCount`, `relatedQuestions`, `relatedQuestionsCount`, `organicResults`, `organicResultsCount`, `organicDomains`, `firstOrganicResult`
`summaryTitle`, `matchedSelector`, `extractionConfidence`, `extractionMethod`, `expandedOverview`, `searchUrl`, `searchMetadata`, `language`, `country`, `scrapedAt`
`aiOverviewText`, `aiOverviewHtml`, `aiOverviewLength`, `hasAiOverview`

</details>

#### Example dataset item

This compact example is taken from local Actor storage. Long text and nested collections are shortened for documentation only.

```json
{
  "position": 1,
  "searchQuery": "what is machine learning",
  "summaryTitle": "Machine learning is a subset of artificial intelligence where algorithms analyze vast amounts of data to detect patterns and make predictions without needing explicit, hard-coded …",
  "aiSummary": "Machine learning is a subset of artificial intelligence where algorithms analyze vast amounts of data to detect patterns and make predictions without needing explicit, hard-coded …",
  "sourcesCount": 2,
  "relatedQuestionsCount": 4,
  "organicResultsCount": 8,
  "extractionConfidence": "high",
  "scrapedAt": "2026-07-23T19:20:34.552Z",
  "type": "ai_overview",
  "query": "what is machine learning",
  "resultType": "google_ai_overview"
}
```

### Related Actors

- [Google About This Result Scraper](https://apify.com/searchapi/google-about-this-result-scraper)
- [Google Autocomplete Scraper](https://apify.com/searchapi/google-autocomplete-scraper)
- [Google Books Scraper](https://apify.com/searchapi/google-books-scraper)

# Actor input Schema

## `queries` (type: `array`):

List of search queries to scrape AI Overviews for.

## `maxItems` (type: `integer`):

Maximum number of results to return.

## `gl` (type: `string`):

Google country parameter (e.g. 'us', 'uk', 'in').

## `hl` (type: `string`):

Google language parameter (e.g. 'en', 'es', 'fr').

## `proxyConfiguration` (type: `object`):

Select proxies to use for the scraper.

## Actor input object example

```json
{
  "queries": [
    "What is quantum computing"
  ],
  "maxItems": 10,
  "gl": "us",
  "hl": "en",
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "GOOGLE_SERP"
    ]
  }
}
```

# Actor output Schema

## `results` (type: `string`):

Structured Google AI Overview answers, citations, related questions, and organic context.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "queries": [
        "What is quantum computing"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("searchapi/google-ai-overview-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "queries": ["What is quantum computing"] }

# Run the Actor and wait for it to finish
run = client.actor("searchapi/google-ai-overview-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "queries": [
    "What is quantum computing"
  ]
}' |
apify call searchapi/google-ai-overview-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=searchapi/google-ai-overview-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/Vhf7jZIs0bniBxXF7/builds/1O3tvHXZQyBqncLlO/openapi.json