# Bing Autocomplete Keyword Suggestions Scraper (`dt_org/dreemteam-bing-autocomplete`) Actor

Collect Bing autocomplete keyword suggestions for SEO research, content planning, and market analysis.

- **URL**: https://apify.com/dt\_org/dreemteam-bing-autocomplete.md
- **Developed by:** [DreamTeam](https://apify.com/dt_org) (community)
- **Categories:** Automation, Developer tools, Other
- **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.30 / 1,000 results

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/platform/actors/running/actors-in-store#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

## Bing Autocomplete Keyword Suggestions Scraper

Collect Bing autocomplete keyword suggestions from seed keywords and turn them
into clean rows for SEO research, content planning, and market analysis.

Use this Actor to discover long-tail keyword ideas, compare search intent,
expand topic clusters, build content briefs, and enrich keyword research
workflows with repeatable Bing suggestion data.

This Actor is unofficial and is not affiliated with, endorsed by, or sponsored
by Microsoft, Bing, or their affiliates.

### What You Can Collect

- Bing autocomplete suggestions for each lookup query.
- The original seed keyword that generated each lookup.
- The exact lookup query used for each suggestion.
- Suggestion position within the returned autocomplete list.
- Collection timestamp and source label for repeatable exports.

### Common Use Cases

- Build SEO keyword lists from short seed terms.
- Find long-tail content ideas around brands, products, and topics.
- Expand paid search and marketplace research terms.
- Compare autocomplete demand across multiple seed keywords.
- Feed keyword suggestions into spreadsheets, BI tools, or enrichment pipelines.

### Input

- `seedKeywords` - base terms, brands, products, categories, or topics to
  research.
- `expansionMode` - choose how lookup queries are generated:
  - `none` uses each seed keyword exactly as entered.
  - `alphabet` appends `a` through `z` to find long-tail variants.
  - `questions` generates buyer and research-style query patterns.
- `maxQueries` - maximum number of generated autocomplete lookups for the run.
- `maxSuggestionsPerQuery` - maximum number of suggestions saved for each
  lookup.
- `deduplicate` - keep only the first occurrence of each suggestion across the
  run.

### Example Input

```json
{
  "seedKeywords": ["web scraping"],
  "expansionMode": "none",
  "maxQueries": 5,
  "maxSuggestionsPerQuery": 10,
  "deduplicate": true
}
```

### Alphabet Expansion Example

```json
{
  "seedKeywords": ["email marketing"],
  "expansionMode": "alphabet",
  "maxQueries": 10,
  "maxSuggestionsPerQuery": 10,
  "deduplicate": true
}
```

### Output

Each dataset row is one useful autocomplete suggestion:

- `seedKeyword`
- `query`
- `position`
- `suggestion`
- `source`
- `collectedAt`

Example row:

```json
{
  "seedKeyword": "web scraping",
  "query": "web scraping",
  "position": 1,
  "suggestion": "web scraping tools",
  "source": "bing",
  "collectedAt": "2026-07-04T00:00:00+00:00"
}
```

The key-value store `OUTPUT` object contains run status, input count, output
count, quota status, warnings, and errors.

### Result Counting

Each autocomplete suggestion is written as one dataset row. Status summaries,
empty results, errors, and quota-limit outcomes are reported in `OUTPUT` and do
not create extra dataset rows.

### Limits

Start with small inputs when testing a new keyword set. Autocomplete suggestions
can vary by time, availability, and source behavior, so repeated runs may return
slightly different suggestion lists.

# Actor input Schema

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

Base terms, brands, products, categories, or topics to research.

## `expansionMode` (type: `string`):

Choose exact seed lookups, alphabet long-tail expansion, or buyer/research question expansion.

## `maxQueries` (type: `integer`):

Maximum number of generated autocomplete lookups for this run.

## `maxSuggestionsPerQuery` (type: `integer`):

Maximum number of suggestions saved for each autocomplete lookup.

## `deduplicate` (type: `boolean`):

Keep only the first occurrence of each suggestion across the run.

## Actor input object example

```json
{
  "seedKeywords": [
    "web scraping"
  ],
  "expansionMode": "none",
  "maxQueries": 50,
  "maxSuggestionsPerQuery": 20,
  "deduplicate": true
}
```

# Actor output Schema

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

Dataset rows. Each row is one autocomplete suggestion with seed and query context.

## `summary` (type: `string`):

Structured run status, counts, quota status, warnings, and errors.

# 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("dt_org/dreemteam-bing-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 = {}

# Run the Actor and wait for it to finish
run = client.actor("dt_org/dreemteam-bing-autocomplete").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).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 dt_org/dreemteam-bing-autocomplete --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=dt_org/dreemteam-bing-autocomplete",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/CeaOOQIn0Eq2IEZbC/builds/ZGbbyPJYt9BWAecSn/openapi.json