# Google Autocomplete Scraper — Keywords & Monitor (`zenomastro/google-autocomplete-keywords`) Actor

Google Autocomplete keyword scraper for long-tail SEO research. Expand seeds with A–Z, numbers, questions, prepositions, comparisons and custom modifiers, recurse through suggestions, run country/language matrices, cap requests/results, and monitor new or disappeared suggestions.

- **URL**: https://apify.com/zenomastro/google-autocomplete-keywords.md
- **Developed by:** [Rosario Vitale](https://apify.com/zenomastro) (community)
- **Categories:** SEO tools, Marketing, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.50 / 1,000 unique autocomplete suggestions

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?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Google Autocomplete Scraper — Long-Tail, Intent & Monitor

### Why use this Actor?

Scrape Google Autocomplete for SEO keyword research with A–Z, numeric, question, preposition and comparison expansion, recursive long-tail discovery, search-intent labels and persistent new/removed keyword monitoring.

#### What you can do

- **Seed keywords** — Seed queries to expand with Google Autocomplete.
- **Language** — Google hl language code, e.g. en, it, de.
- **Country** — Google gl country code, e.g. US, IT, GB.
- **Append A-Z** — Query seed + each letter a-z.
- **Prepend A-Z** — Query each letter + seed for extra discovery.
- **Append 0-9** — Also query seed + digits 0-9 for numeric long-tail variations.
- **Question prefixes** — Add how/what/why/when/where/who/which/can/does/is/best prefixes.
- **Maximum unique suggestions** — Hard cap on unique paid suggestion rows emitted across all seeds.
- **Maximum Google requests** — Hard cap on Google Suggest requests for predictable runtime and request volume.
- **Delay between requests (ms)** — Delay between Google Suggest requests to reduce burst rate.
- **Request timeout** — Maximum seconds allowed for each Google Suggest HTTP request.
- **Retries** — Retries each failed Suggest request after transient network or HTTP errors.

#### Best for

- Seo keyword research.
- Long-tail discovery.
- Content planning.
- Search-intent and trend monitoring.

#### FAQ

**What is this Actor for?**\
It is designed for SEO keyword research, long-tail discovery, content planning.

**Can I run it on a schedule?**\
Yes. You can schedule Actor runs on Apify and send the resulting dataset into automations, webhooks, storage, or downstream APIs.

**How do I control cost and run size?**\
Use the input limits and filters shown in the Actor input form. The Actor applies bounded defaults and hard caps so large jobs remain predictable.

#### Search keywords

google autocomplete scraper, google suggest scraper, google autocomplete scraping, turn off google autocomplete, google autocomplete not working, keyword scraper tool, research keywords example, what is keyword research, google, autocomplete, keyword, suggestions, long-tail, seo

Turn seed queries into structured Google Autocomplete keyword ideas for SEO, PPC, content planning, market research and AI workflows.

The Actor uses Google's public Suggest response directly. It does not render SERPs, does not require a Google API key, and supports bounded expansion so cost and request volume stay predictable.

### Features

- bulk seed keywords
- Google language and country localization
- base suggestions plus A-Z expansion
- optional 0-9 expansion
- optional question prefixes such as how, what, why, where and best
- optional A-Z prefix expansion
- global deduplication per seed/localization
- Google source rank and suggest subtype metadata
- retries, request timeout and polite delay
- request and result hard caps
- pay only for successful unique suggestion rows
- free diagnostic and summary rows

### Example input

```json
{
  "seeds": ["best laptop", "ai tools"],
  "language": "en",
  "country": "US",
  "expandAlphabet": true,
  "expandQuestions": true,
  "expandNumbers": false,
  "maxSuggestions": 2000
}
```

### Pricing

Launch target: **$0.00049 per unique suggestion** (about **$0.49 / 1,000 suggestions**) plus the small Actor-start event. Duplicate suggestions, failed requests and the summary row are free.

### Responsible use

Google controls the public Suggest endpoint and may change response behavior or rate limits. Keep request caps and delay enabled for large jobs and use the data in accordance with applicable terms and laws.

# Actor input Schema

## `seeds` (type: `array`):

Seed queries to expand with Google Autocomplete.

## `language` (type: `string`):

Google hl language code, e.g. en, it, de.

## `country` (type: `string`):

Google gl country code, e.g. US, IT, GB.

## `expandAlphabet` (type: `boolean`):

Query seed + each letter a-z.

## `prependAlphabet` (type: `boolean`):

Query each letter + seed for extra discovery.

## `expandNumbers` (type: `boolean`):

Also query seed + digits 0-9 for numeric long-tail variations.

## `expandQuestions` (type: `boolean`):

Add how/what/why/when/where/who/which/can/does/is/best prefixes.

## `maxSuggestions` (type: `integer`):

Hard cap on unique paid suggestion rows emitted across all seeds.

## `maxRequests` (type: `integer`):

Hard cap on Google Suggest requests for predictable runtime and request volume.

## `delayMs` (type: `integer`):

Delay between Google Suggest requests to reduce burst rate.

## `requestTimeoutSecs` (type: `integer`):

Maximum seconds allowed for each Google Suggest HTTP request.

## `retries` (type: `integer`):

Retries each failed Suggest request after transient network or HTTP errors.

## `expandPrepositions` (type: `boolean`):

Expand seed + for/with/without/near/vs/like/to/from/in.

## `expandComparisons` (type: `boolean`):

Expand comparison, alternative and competitor long-tail patterns.

## `recursiveDepth` (type: `integer`):

Use returned suggestions as new queries for deeper long-tail discovery. Request caps still apply.

## `maxSuggestionsPerSeed` (type: `integer`):

Per-seed safety cap before moving to the next seed.

## `monitorKey` (type: `string`):

Reuse a stable key on scheduled runs to detect newly appeared and disappeared suggestions.

## `onlyNew` (type: `boolean`):

With monitorKey, bill/output only suggestions not seen in the previous snapshot.

## `languages` (type: `array`):

Optional multiple Google hl language codes. When set, runs every language × country combination; otherwise the single language field is used.

## `countries` (type: `array`):

Optional multiple Google gl country codes. When set, runs every language × country combination; maximum 100 combinations.

## `customPrefixes` (type: `array`):

Optional custom words or phrases queried before each seed, e.g. how to, best, free.

## `customSuffixes` (type: `array`):

Optional custom words or phrases queried after each seed, e.g. software, near me, for beginners.

## Actor input object example

```json
{
  "seeds": [
    "artificial intelligence"
  ],
  "language": "en",
  "country": "US",
  "expandAlphabet": true,
  "prependAlphabet": false,
  "expandNumbers": false,
  "expandQuestions": true,
  "maxSuggestions": 5000,
  "maxRequests": 500,
  "delayMs": 120,
  "requestTimeoutSecs": 15,
  "retries": 2,
  "expandPrepositions": true,
  "expandComparisons": false,
  "recursiveDepth": 1,
  "maxSuggestionsPerSeed": 2000,
  "monitorKey": "",
  "onlyNew": false,
  "languages": [],
  "countries": [],
  "customPrefixes": [],
  "customSuffixes": []
}
```

# Actor output Schema

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

No description

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("zenomastro/google-autocomplete-keywords").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("zenomastro/google-autocomplete-keywords").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 '{}' |
apify call zenomastro/google-autocomplete-keywords --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,zenomastro/google-autocomplete-keywords"
        }
    }
}
```

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/DF5RpM9XoHTXYyimN/builds/QeNPI74S5K5Obn021/openapi.json