Google Search: scrapers and the official API, compared

Route map

Each line is one way to get Google Search data; each stop is a field you probably need. Green lines are catalogue Actors, ranked by the published formula.

Which route for which job

The catalogue Actors for Google Search return different records. "Only this route" lists the published fields no other Actor in this table returns, which is usually what decides the choice. Cost is the published per-result rate; start events and platform usage are extra.

Field matrix: who returns what

Every tool with a published output schema, against the 5 fields most Google Search jobs need. A dot means the field name appears in the schema; rows can still leave it empty.

Field dictionary: the exact keys

The same core field has a different key in each Actor's output. Map these before you merge datasets; a dash means the published schema has no matching key. Need a field that is not listed here, such as email? Search every Google Search Actor by field.

Download this comparison: CSV · JSON (every tool with a published schema, matching keys per core field, price and score).

All 13 tools, scored

Catalogue Actors link to their detail pages; the score (0 to 100) is the published formula, identical for every tool. Other Store tools follow in their own table, for reference. Price is the published primary-result rate per 1,000 (the Free-plan rate where the price is tiered; higher Apify plans pay less); start events and platform usage are excluded.

Other Store tools, for reference

Scored with the same published formula and listed for comparison only; this site does not link or recommend them.

What to check before you choose

Search teams use Google results to track visible pages, study competing content and identify questions around a topic. Research teams use destination links to build reading lists and collect source material.

Choose a results collector for rankings and search features, an autocomplete tool for phrase discovery, or a page extractor for destination content. The programmable search API suits a configured search engine rather than reproducing the live Google results page.

Checklist

• Verify the query, country and pagination controls, and keep that context with every ranking dataset.
• Check whether the schema contains full result groups such as organicResults and peopleAlsoAsk or only image records, suggestions or destination-page metadata.
• For image results, inspect engine, retrievalMethod, isFallback and fallbackReason before attributing rows to Google.

Where the data is incomplete

The published data does not define the nested fields inside organicResults, so confirm their structure before mapping individual results.

The leading tool's detailed schema is absent from the published data. The image tool also documents fallback results from another engine, which need to be distinguished from Google results when measuring search visibility.

Official API route

Terms and personal data

Collect ranking data from public pages and follow Google's terms. Check the conditions for storing and reusing result snippets and destination content. This is general information, not legal advice.

Read Google Search's terms. Keep to public data, do not bypass logins or access controls, and check whether personal data is involved before you collect it. The can-I-scrape checklist walks through it.

How to start

1. Open the recommended Google Search tool and check its documented query inputs. Choose a narrow query and record any supported country or language settings.
2. Collect a small dataset and inspect how it represents result positions, destination links and search features. Confirm the producing engine wherever the output identifies it.
3. Save the dataset with its query settings and collection time. Preserve result groups and position information when preparing the first analysis.

Call Search & URL Markdown Extractor for LLMs from code

The example input uses the Actor's published defaults; set your own Google Search query before you run it. You need an Apify API token.

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run_input = {
    "query": "what is retrieval augmented generation",
    "queries": [],
    "startUrls": [],
    "searchEngine": "auto",
    "searchLanguage": "auto",
    "searchCountry": "auto",
    "maxResults": 3,
    "maxItems": 0,
    "outputFormats": [
        "markdown"
    ],
    "removeElementsCssSelector": "nav, footer, aside, script, style, .ad, .advertisement, [aria-hidden='True']",
    "keepElementsCssSelector": [],
    "htmlTransformer": "readable-text",
    "maxContentLength": 0,
    "includeMetadata": True,
    "chunkMarkdown": False,
    "chunkMaxChars": 2000,
    "chunkOverlapChars": 200,
    "maxCrawlDepth": 0,
    "maxCrawlPages": 25,
    "domainAllowlist": [],
    "domainBlocklist": [],
    "excludeContentSelectors": [],
    "keywordsAnyOf": [],
    "emitFailedResults": False
}

run = client.actor("vexaloom-labs/rag-web-browser").call(run_input=run_input)
if run is None:
    raise RuntimeError("The Actor run was not found.")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "<YOUR_APIFY_TOKEN>" });
const input = {
    "query": "what is retrieval augmented generation",
    "queries": [],
    "startUrls": [],
    "searchEngine": "auto",
    "searchLanguage": "auto",
    "searchCountry": "auto",
    "maxResults": 3,
    "maxItems": 0,
    "outputFormats": [
        "markdown"
    ],
    "removeElementsCssSelector": "nav, footer, aside, script, style, .ad, .advertisement, [aria-hidden='true']",
    "keepElementsCssSelector": [],
    "htmlTransformer": "readable-text",
    "maxContentLength": 0,
    "includeMetadata": true,
    "chunkMarkdown": false,
    "chunkMaxChars": 2000,
    "chunkOverlapChars": 200,
    "maxCrawlDepth": 0,
    "maxCrawlPages": 25,
    "domainAllowlist": [],
    "domainBlocklist": [],
    "excludeContentSelectors": [],
    "keywordsAnyOf": [],
    "emitFailedResults": false
};

const run = await client.actor("vexaloom-labs/rag-web-browser").call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

curl -X POST "https://api.apify.com/v2/actors/vexaloom-labs~rag-web-browser/run-sync-get-dataset-items"   -H "Authorization: Bearer $APIFY_TOKEN"   -H "Content-Type: application/json"   -d '{"query":"what is retrieval augmented generation","queries":[],"startUrls":[],"searchEngine":"auto","searchLanguage":"auto","searchCountry":"auto","maxResults":3,"maxItems":0,"outputFormats":["markdown"],"removeElementsCssSelector":"nav, footer, aside, script, style, .ad, .advertisement, [aria-hidden='''true''']","keepElementsCssSelector":[],"htmlTransformer":"readable-text","maxContentLength":0,"includeMetadata":true,"chunkMarkdown":false,"chunkMaxChars":2000,"chunkOverlapChars":200,"maxCrawlDepth":0,"maxCrawlPages":25,"domainAllowlist":[],"domainBlocklist":[],"excludeContentSelectors":[],"keywordsAnyOf":[],"emitFailedResults":false}'

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=vexaloom-labs/rag-web-browser",
      "headers": {
        "Authorization": "Bearer <YOUR_APIFY_TOKEN>"
      }
    }
  }
}

Questions people ask

More on Google Search

• Official API pricingGoogle Custom Search JSON API: 100 free queries a day, ends 2027
• AlternativesSerpApi alternatives after Google's December 2025 lawsuit
• Topic groupLocal business data: every website compared
• ToolWhich Google Search route fits your job?
• ToolGoogle Search cost by Apify plan, rows and runs

Related websites

• Bing3 Actors
• Yandex4 Actors
• Naver5 Actors
• Baidu1 Actor

Sources

• Search & URL Markdown Extractor for LLMs on Apify Store
• Google Image Search Results & Metadata Scraper on Apify Store
• Google Autocomplete Keyword Expansion Scraper on Apify Store
• Google Search Results Scraper: Organic & SERP Boxes on Apify Store
• Programmable Search Engine JSON API documentation
• Programmable Search Engine JSON API pricing
• Google Search terms