# Keyword Research: Google, YouTube, Amazon Autocomplete (`torix33/keyword-research-autocomplete`) Actor

Find hundreds of long-tail keywords and questions per seed from Google, YouTube, Amazon, Bing, DuckDuckGo and Google Shopping autocomplete (a–z, question and buyer-intent expansion), with search intent, source count and rank. For SEO, content, PPC and Amazon listings. Pay per keyword.

- **URL**: https://apify.com/torix33/keyword-research-autocomplete.md
- **Developed by:** [Torix](https://apify.com/torix33) (community)
- **Categories:** SEO tools, Marketing, AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.10 / 1,000 keyword scrapeds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

## Keyword Research — Google, YouTube, Amazon & Bing Autocomplete

Turn a seed keyword into **hundreds of real long-tail keywords and questions** people type into **Google, YouTube, Amazon, Bing, DuckDuckGo and Google Shopping**.

Each seed is expanded with **a–z / 0–9**, **question words** (how, what, why…) and **buyer-intent modifiers** (best, cheap, vs, near me, price, alternative…). Every keyword comes with:

**search intent (informational / commercial / transactional / navigational), question flag, word count, which sources suggested it, how many sources agree, best autocomplete position, and the query that surfaced it.**

### How to run it in 3 steps

1. **Add your input.** In **Seed keywords** paste seed keywords, one per line — e.g. `coffee maker`. The form is already filled with a working example, so you can skip this step for a first try.
2. **Press Start.** The prefilled run returns 30 keywords in about 4 s and costs about **$0.090**. Set **Max results (cost cap)** to cap the cost of bigger runs; you only pay for keywords actually delivered.
3. **Get the data.** Open the **Output** tab and export JSON, CSV or Excel — or run it from the API, Make, Zapier, n8n or an AI agent (see below).

### Features

- **6 sources in one run**, merged and deduplicated — keywords suggested by several engines are ranked first.
- **Fast:** ~250 autocomplete queries per seed in a few seconds (2 seeds → 1,879 keywords in 5 s in our test).
- **Ready to use:** intent and question tags for content plans, PPC ad groups and Amazon listing keywords.
- **Pay per keyword:** $3 per 1,000 keywords. Cap it with `maxKeywordsPerSeed`.

### Use cases

- **SEO & content:** find questions to answer and long-tail topics to rank for.
- **YouTube SEO:** titles and tags people actually search for.
- **Amazon sellers:** backend keywords and listing copy from Amazon's own suggestions.
- **PPC:** build ad groups by intent; find negative keywords.

### Input

```json
{
  "seedKeywords": ["coffee maker", "crm software"],
  "sources": ["google", "youtube", "bing", "amazon"],
  "alphabet": true,
  "questions": true,
  "modifiers": true,
  "country": "us",
  "language": "en",
  "maxKeywordsPerSeed": 300
}
```

### Output

#### Real output (default input)

First 2 of 30 records from a run with the prefilled input (3.3 s on a test machine; long values shortened here):

```json
[
  {
    "keyword": "best coffee maker",
    "seed": "coffee maker",
    "isQuestion": false,
    "intent": "commercial",
    "wordCount": 3,
    "length": 17,
    "sources": [
      "google",
      "youtube",
      "bing"
    ],
    "sourceCount": 4,
    "bestPosition": 1,
    "foundVia": [
      "best coffee maker",
      "top coffee maker"
    ],
    "language": "en",
    "country": "us"
  },
  {
    "keyword": "best coffee maker 2026",
    "seed": "coffee maker",
    "isQuestion": false,
    "intent": "commercial",
    "wordCount": 4,
    "length": 22,
    "sources": [
      "bing",
      "amazon",
      "google"
    ],
    "sourceCount": 4,
    "bestPosition": 1,
    "foundVia": [
      "coffee maker 2",
      "best coffee maker"
    ],
    "language": "en",
    "country": "us"
  }
]
```

```json
{
  "keyword": "best coffee maker 2026",
  "seed": "coffee maker",
  "intent": "commercial",
  "isQuestion": false,
  "wordCount": 4,
  "sources": ["bing", "amazon", "google", "youtube"],
  "sourceCount": 4,
  "bestPosition": 1,
  "foundVia": ["coffee maker 2", "best coffee maker"]
}
```

Autocomplete shows what people search for, not search volumes — combine with your favourite volume tool.

### Pricing

- **$3.00 per 1,000 keywords** ($0.003 per keyword).
- The prefilled input returns 30 keywords → **$0.09**.
- Example: 1,000 keywords → $3.00; 10,000 → $30.00. Set **Max results (cost cap)** to limit any run.

* Duplicates across sources are free.
* Your Apify spending limit is respected exactly: the actor stops charging and finishes cleanly when it is reached. Apify platform usage (compute, proxy) is included in the price.

### Use with AI agents (MCP), LangChain, RAG & the API

This actor is a ready-made **tool for AI agents**: an LLM can call it, wait for the run and read clean JSON back.

**MCP server (Claude Desktop, Claude Code, Cursor, VS Code, any MCP client)** — add Apify's hosted MCP server with this actor enabled as a tool:

```json
{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?tools=torix33/keyword-research-autocomplete",
      "headers": { "Authorization": "Bearer <APIFY_TOKEN>" }
    }
  }
}
```

**LangChain / LangGraph** (`pip install langchain-apify`, set `APIFY_API_TOKEN`):

```python
import json
from langchain_apify import ApifyActorsTool, ApifyWrapper
from langchain_core.documents import Document

## 1) give the actor to an agent as a tool
tool = ApifyActorsTool("torix33/keyword-research-autocomplete")

## 2) or load results as Documents for a RAG index
loader = ApifyWrapper().call_actor(
    actor_id="torix33/keyword-research-autocomplete",
    run_input={"seedKeywords": ["coffee maker", "crm software"], "sources": ["google", "youtube", "bing", "amazon"], "alphabet": True, "questions": True, "modifiers": True, "country": "us", "language": "en", "maxKeywordsPerSeed": 300},
    dataset_mapping_function=lambda item: Document(page_content=json.dumps(item, ensure_ascii=False), metadata={"url": item.get("url")}),
)
docs = loader.load()
```

**REST API — one synchronous call, dataset items in the response:**

```bash
curl -X POST "https://api.apify.com/v2/acts/torix33~keyword-research-autocomplete/run-sync-get-dataset-items?token=<APIFY_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"seedKeywords": ["coffee maker", "crm software"], "sources": ["google", "youtube", "bing", "amazon"], "alphabet": true, "questions": true, "modifiers": true, "country": "us", "language": "en", "maxKeywordsPerSeed": 300}'
```

Also works with the Apify Python/JS clients, **Make, Zapier, n8n**, Google Sheets, webhooks and schedules. Export as JSON, CSV, Excel, XML or RSS.

**RAG tip:** Give an agent the deduplicated `keyword` list with `intent` tags and let it cluster them into a content plan or PPC ad groups.

### Limitations

- Autocomplete has no search volumes; keywords suggested by several engines are ranked first as a popularity signal.
- Suggestions differ by country and language — set them to match your market.
- At most `maxKeywordsPerSeed` keywords per seed.

### FAQ

**Is it a Keywordtool.io alternative?**
Yes — it collects autocomplete suggestions from several engines in one run at $3 per 1,000 keywords.

**Does it return search volume?**
No. Autocomplete data has no volumes; keywords suggested by several engines are ranked first as a popularity signal.

**Can I get question keywords?**
Yes. Turn on `questions` for who / what / how / why style suggestions.

# Actor input Schema

## `seedKeywords` (type: `array`):

Topics to expand, one per line.

## `sources` (type: `array`):

Where suggestions come from. Keywords found in several sources are ranked higher.

## `alphabet` (type: `boolean`):

Query "seed a" … "seed z", "seed 0" … "seed 9".

## `questions` (type: `boolean`):

Query how / what / why / when / where / which / who / can / is … + seed.

## `modifiers` (type: `boolean`):

Query best / cheap / top / vs / for / near me / review / price / alternative …

## `deepExpand` (type: `boolean`):

Also expand the 50 strongest first-level keywords (more long-tail results, ~2x queries).

## `mustContainSeed` (type: `boolean`):

Drop suggestions that don't contain every word of the seed.

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

Language code, e.g. <code>en</code>, <code>de</code>, <code>es</code>.

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

Country code, e.g. <code>us</code>, <code>gb</code>, <code>de</code>. (Amazon suggestions are amazon.com.)

## `maxKeywordsPerSeed` (type: `integer`):

Keep the strongest N keywords per seed (ranked by number of sources, then position).

## `maxResults` (type: `integer`):

Stop after this many keywords in total. <code>0</code> = no limit.

## `maxConcurrency` (type: `integer`):

Autocomplete requests in parallel.

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

Datacenter proxy is used only for retries.

## Actor input object example

```json
{
  "seedKeywords": [
    "coffee maker"
  ],
  "sources": [
    "google",
    "youtube",
    "bing",
    "amazon"
  ],
  "alphabet": true,
  "questions": true,
  "modifiers": true,
  "deepExpand": false,
  "mustContainSeed": false,
  "language": "en",
  "country": "us",
  "maxKeywordsPerSeed": 30,
  "maxResults": 0,
  "maxConcurrency": 20,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# Actor output Schema

## `keywords` (type: `string`):

No description

## `runStats` (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 = {
    "seedKeywords": [
        "coffee maker"
    ],
    "maxKeywordsPerSeed": 30,
    "proxyConfiguration": {
        "useApifyProxy": true
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("torix33/keyword-research-autocomplete").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 = {
    "seedKeywords": ["coffee maker"],
    "maxKeywordsPerSeed": 30,
    "proxyConfiguration": { "useApifyProxy": True },
}

# Run the Actor and wait for it to finish
run = client.actor("torix33/keyword-research-autocomplete").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 '{
  "seedKeywords": [
    "coffee maker"
  ],
  "maxKeywordsPerSeed": 30,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}' |
apify call torix33/keyword-research-autocomplete --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,torix33/keyword-research-autocomplete"
        }
    }
}
```

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/sg8h83751ARDAdkx0/builds/YurWaXaaN6MU04FUb/openapi.json