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

Collect AI-generated answers from Google Search along with cited sources, referenced websites, and follow-up queries to analyze AI search visibility and content opportunities.

- **URL**: https://apify.com/scrapeai/google-ai-overview-scraper.md
- **Developed by:** [ScrapeAI](https://apify.com/scrapeai) (community)
- **Categories:** AI, SEO tools, Developer tools
- **Stats:** 69 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $5.00 / 1,000 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/actors/running/actors-in-store.md#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

Extract Google's AI Overview content from search results, capturing generated summaries, source references, citations, and supporting information.

### Features

- **Search AI content collection** — retrieve AI-generated summaries and answer panels from Google Search
- **Source attribution capture** — extract citations and linked resources used in AI responses
- **Follow-up question extraction** — gather additional questions users may explore next
- **Designed for Apify cloud** — supports automation, proxy rotation, APIs, and webhook integrations

### Use Cases

- AI search trend analysis — understand how AI-generated search experiences impact keyword visibility and search behavior
- Answer evolution tracking — compare AI-generated responses over time for consistency and accuracy monitoring
- Knowledge dataset development — gather AI-generated content and citations for academic, commercial, or technical research
- Real-time change detection — trigger alerts when AI Overview availability or content changes significantly

#### Sample Output

```json
{
  "query": "best programming languages 2025",
  "hasAiOverview": true,
  "aiOverviewText": "In 2025, the most popular programming languages include Python for data science and AI, JavaScript for web development, Rust for systems programming...",
  "sources": [
    "https://www.tiobe.com/tiobe-index/",
    "https://stackoverflow.blog/2024/developer-survey"
  ],
  "relatedQuestions": ["Which language should I learn first?", "Is Python better than Java?"],
  "searchUrl": "https://www.google.com/search?q=best+programming+languages+2025",
  "scrapedAt": "2025-01-15T10:30:00.000Z"
}
```

# Actor input Schema

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

List of search queries to scrape AI Overview answers 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": 5,
  "gl": "us",
  "hl": "en",
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}
```

# 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("scrapeai/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("scrapeai/google-ai-overview-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).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 scrapeai/google-ai-overview-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapeai/google-ai-overview-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/3zojazQiEX4QCbBYx/builds/AJvPVTyfNsTPAJtRR/openapi.json