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Google Autocomplete Scraper

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from $0.01 / 1,000 keyword suggestions

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Google Autocomplete Scraper

Google Autocomplete Scraper

Collect Google autocomplete keyword suggestions by seed query, language, and country.

Pricing

from $0.01 / 1,000 keyword suggestions

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Fetch Cat

Fetch Cat

Maintained by Community

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2

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2 days ago

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Export Google autocomplete suggestions from seed keywords, with each suggestion's order, language, country and source URL. Use this Google Autocomplete Scraper for long-tail keyword research, content planning and PPC ideas—not search-volume estimates or keyword difficulty.

Quick start

  1. Enter one or more seed phrases in Seed keywords.
  2. Choose a language and country, or keep English and United States.
  3. Start the Actor, then open its dataset and export CSV, Excel or JSON.

Start with a small input:

{
"queries": ["standing desk", "office chair"],
"language": "en",
"country": "us",
"maxSuggestionsPerQuery": 10
}

Google may return fewer suggestions than requested. Results vary over time and are not a complete list of searches people make.

Prefer a video guide? This short Apify walkthrough shows you how to set up and run an Actor. It uses a different Actor, but the setup steps are the same.

Ready-to-run examples

Choose a public example to see its settings before starting a run:

What you get

One row per saved suggestion, with its seed phrase, returned order, requested locale and client, source URL and fetch time. These are current autocomplete observations rather than search-volume, demand or popularity measurements.

Who is it for?

  • Keyword researchers collecting phrase ideas for later investigation.
  • Content teams preparing topic or question shortlists in their own tools.
  • PPC researchers reviewing wording variations before separate evaluation.
  • Market researchers comparing bounded country/language observations.

How you can use the data

  • Prepare an office-product phrase sheet. Use the existing standing-desk and office-chair seeds with a small per-seed cap. Keep query, suggestion, rank, sourceUrl and fetchedAt together before grouping ideas in your own planning sheet.
  • Review a local-service wording sample. Use the existing dentist example or a specific service phrase with the intended country and language. Treat suggestions as wording ideas rather than evidence of demand, expected traffic or conversion.
  • Compare locales through separate runs. Repeat the same seeds for each chosen country and language, keeping those settings with your exports. Interpret differences as source observations rather than a global popularity ranking.
  • Validate ideas in a separate workflow. Group returned phrases into topics or questions yourself and review any external metrics separately. This Actor does not calculate volume, CPC, difficulty or relevance scores.

Input settings

SettingJSON keyPurpose
Seed keywordsqueriesRequired list of phrases. Up to 1,000 unique seeds.
LanguagelanguageLanguage code. Default en.
CountrycountryCountry code. Default us.
Suggestions per seedmaxSuggestionsPerQuerySave up to 1–20 per seed. Default 10.
Autocomplete clientclientfirefox (default), chrome or toolbar.
Request delayrequestDelayMsPause between seeds. Default 250 ms.
Retries per seedmaxRetriesDefault 2.
Use Apify ProxyuseProxyOptional proxy routing. Off by default.
Proxy groupsproxyGroupsOptional groups used when proxy routing is enabled.

Blank seeds are ignored and repeated seeds are combined without regard to capitalization. Suggestions retain Google's returned order. This is not a search-volume or popularity ranking. See the input-field help for connection settings and limits.

Example inputs

Use the Quick start input as a small first run. Adjust the fields described above for your own data.

Output data

Each dataset row contains one suggestion. This illustrative shape shows the fields, not a recorded result or a guaranteed suggestion:

{
"query": "standing desk",
"suggestion": "standing desk accessories",
"rank": 1,
"language": "en",
"country": "us",
"client": "firefox",
"sourceUrl": "https://suggestqueries.google.com/complete/search?client=firefox&q=standing+desk&hl=en&gl=us",
"fetchedAt": "2026-10-24T12:00:00.000Z"
}
FieldMeaning
queryTrimmed seed phrase associated with the suggestion.
suggestionSuggestion text returned by Google.
rankOne-based position within that seed's saved suggestions.
language, country, clientRequested locale and client settings.
sourceUrlSource URL for the seed lookup.
fetchedAtFetch time in ISO date-time format.

Download your results

Open your run's dataset, choose Export and select JSON, CSV or Excel. JSON keeps nested fields together. CSV and Excel are useful when you want to review the records in a spreadsheet.

See Apify's download and export guide for the available formats and field options.

Pricing

Pay-per-event pricing uses a one-time start charge per run and a result event per suggestion saved. A run can incur the start charge even if it saves no suggestions.

Check the live Pricing tab for current rates and applicable discounts.

Tips for best results

  • Start with a few specific seeds and a small per-seed cap. A larger ceiling cannot create suggestions Google does not return.
  • Keep language and country settings with each export. Use separate runs when comparing locales.
  • Preserve returned order without overinterpreting it. Rank is the suggestion's saved position for its seed rather than search-volume rank.
  • Use the supported request-delay setting for paced batches. Source throttling can still affect availability.
  • Check pending queries before repeating a large input. Not every seed is necessarily processed before a run stops.

Limits and caveats

The Actor collects autocomplete suggestions only, without search volume, CPC, keyword difficulty, relevance scores or recursive expansion. Suggestions are not a complete list of searches or a popularity ranking.

Blank seeds are ignored and repeated seeds are combined without regard to case. Suggestions retain Google's order, and fewer rows than the per-seed cap can be returned.

Google can throttle requests or return no suggestions for some seeds while others produce useful rows. In the current version, a run with no saved suggestions fails. That outcome does not prove a phrase has no demand.

Large batches can stop before every seed is processed. Inspect the dataset, logs and pending-query record before repeating work. Results vary over time and across requested locales.

No Google login or cookies are required, and this is not an official Google API. Topic grouping, metric validation, historical comparisons and alerts belong in your own workflow.

Automation and integrations

Save your settings for next time

Once you have an input that works for you, save it as an Apify task. This keeps your settings together so you can use them again without filling in the form from scratch.

Run on a schedule

Need fresh results regularly? You can schedule the Actor or a saved task to run at a time that suits you.

Each scheduled run collects the data again. If you want to compare results or highlight changes, add that step in your own workflow.

Send results to your other tools

Use n8n, Make or Zapier to connect this scraper to the rest of your workflow. For example, you could pass its results to an AI assistant or add records to a spreadsheet. Follow the Apify integration guides for your chosen tool.

For a custom connection, an Apify webhook can notify your app when a run finishes or fails. Your app can then fetch the results or handle the failure.

API usage

Want to collect this data from your own app or automation? The examples below send input to the scraper and show how to collect its results.

The Node.js and Python examples wait for the run to finish before reading its results. The cURL example starts the run and returns its details. Wait for that run to finish, then use its defaultDatasetId to fetch the results.

For setup instructions, see Apify's JavaScript client guide, Python client guide and Actor runs API reference.

cURL

curl -X POST 'https://api.apify.com/v2/acts/fetch_cat~google-autocomplete-scraper/runs' \
-H "Authorization: Bearer $APIFY_TOKEN" \
-H 'Content-Type: application/json' \
--data @- <<'JSON'
{
"queries": [
"standing desk",
"office chair"
],
"language": "en",
"country": "us",
"maxSuggestionsPerQuery": 10
}
JSON

Node.js

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('fetch_cat/google-autocomplete-scraper').call({
"queries": [
"standing desk",
"office chair"
],
"language": "en",
"country": "us",
"maxSuggestionsPerQuery": 10
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

import os
from apify_client import ApifyClient
client = ApifyClient(os.environ['APIFY_TOKEN'])
run = client.actor('fetch_cat/google-autocomplete-scraper').call(run_input={'queries': ['standing desk', 'office chair'], 'language': 'en', 'country': 'us', 'maxSuggestionsPerQuery': 10})
print(client.dataset(run['defaultDatasetId']).list_items().items)

API and AI-agent usage notes

Wait for the run to finish, then read items from the dataset identified by defaultDatasetId in the run response. Use the Apify API documentation for run status and dataset export.

MCP and AI agents

You can ask your AI assistant to collect data with Google Autocomplete Scraper and help you work with the results. The scraper returns the data, and your assistant can then summarize it, compare records or prepare notes.

Connect your assistant through the Apify MCP server. MCP gives your assistant a way to find this scraper, run it and read the results. Follow the official setup and sign-in guide for your app.

Easier setup with an Apify plugin

If you use a supported coding assistant, the official Apify plugin can set up the connection for you. It connects your assistant to Apify and includes instructions for common tasks. Follow the guide for your particular app.

Use Apify AI in Console

Prefer to keep everything in Apify? Open Apify AI in Console and ask it to find Fetch Cat's Google Autocomplete Scraper. You can describe the data you want and ask questions about the results.

Apify AI is currently in beta. It asks for confirmation before starting an Actor, and normal run charges apply.

Choose your assistant

Connect just this scraper

To keep your setup focused on this scraper, add this server configuration to a compatible MCP client:

{
"mcpServers": {
"apify": {
"url": "https://mcp.apify.com?tools=fetch_cat/google-autocomplete-scraper"
}
}
}

Sign in to Apify when your client asks. If your client uses a Bearer token instead, follow its setup guide and keep the token in its secure configuration. Configuration formats vary by app, so use the linked guide if your client needs a different format.

Use Apify's general server

Already connected to the general Apify MCP server at https://mcp.apify.com? You can use it to find this scraper without adding another server. Ask your assistant to use Google Autocomplete Scraper by Fetch Cat, or give it the identifier fetch_cat/google-autocomplete-scraper.

Your assistant can check the available settings and retrieve the results from the returned run. If the run is still working, it should follow that run rather than start it again. Both connection options use Apify's hosted service.

Example requests

  • “Use Fetch Cat’s Google Autocomplete Scraper to collect up to 5 suggestions each for standing desk and office chair in English for the US. Show seed, suggestion, returned position and source link without estimating search volume.”
  • “Collect at most 5 suggestions for dentist in the country and language I provide. Keep locale settings and fetch time beside each phrase for a wording shortlist, without claiming demand or CPC.”
  • “Retrieve up to 3 suggestions for my supplied product phrase using the second locale I specify. Keep the returned order and source context so I can compare it with my own earlier locale export, without inventing popularity scores.”

Normal Apify charges apply. Check the live Pricing tab before asking your assistant to run a larger batch.

Pay with x402

If your AI agent has a funded wallet, it can pay for Apify usage through x402. This experimental option lets an agent use Apify without a conventional account.

Apify AGI provides a prepaid API token with a spending cap after payment. Your agent can use that token to run this scraper through the Apify API or an authenticated MCP connection.

Some MCP setups also support paying for each request directly. That is a different payment option, so check the official guide for its availability.

Follow the official guide for wallet setup, supported payment options and current terms. Apify handles the payments. Keep wallet keys and payment tokens in your agent's secure configuration.

Other ways for agents to pay

Apify also supports MPP for prepaid access through AGI and Skyfire for eligible Actors. If your agent already uses one of these, see the agentic payment guide to choose the right setup.

FAQ

Can I use this as a Google Autocomplete API alternative?

Yes, for exporting suggestions through Apify. It does not provide an official Google API or Google account access.

Can I export Google autocomplete to CSV or Excel?

Yes. Export the finished run's dataset as CSV, Excel or JSON, or retrieve it through the Dataset API.

Does this include keyword search volume?

No. Suggestions are phrase ideas, not measured demand, traffic or keyword difficulty.

Why are some seeds missing from the dataset?

Google may return no suggestions for a seed, especially a specific long phrase. A completed batch with valid empty responses succeeds with an empty dataset. The RUN_SUMMARY key-value record lists each seed as results, empty or failed, with a reason and suggestion count. Request failures, blocked responses and malformed data fail the run while preserving completed results. If the run reaches its time limit, unfinished seeds are listed in PENDING_QUERIES. Do not assume an empty response means no searches exist.

Support and feedback

For custom additions or integrations, email hello@fetchcat.dev.

Found an error or have a feature request? Open an issue with the run URL, a non-sensitive input example and what you expected.

Need help sharing it? See Apify’s guide to sharing a run when reporting an issue. Sharing a run can give the developer access to its input, logs and results, so use a run that contains no sensitive data. Please leave out API tokens, passwords, cookies, private documents and personal data. Use a public sample URL or a redacted example instead.

Tried this scraper? We'd love to hear how it worked for you. Leave a review to help others choose the right tool and help us improve it. Your feedback means a lot to us.

Made with care for curious people, AI agents and the possibilities in data. ♥