# Steam Game Search Suggest Scraper (`emreyilmaz/steam-game-search-suggest`) Actor

Get live Steam search suggestions for any keyword. Long-tail keyword research with a-z expansion and CSV export.

- **URL**: https://apify.com/emreyilmaz/steam-game-search-suggest.md
- **Developed by:** [Emre Yılmaz](https://apify.com/emreyilmaz) (community)
- **Categories:** Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage

## 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

## Steam Game Search Suggest Scraper

Get **live Steam search suggestions** for any seed keyword — the exact phrases Steam shows
people as they type. The fastest way to see **real demand** in Steam's own words.

### Why Steam suggestions?

Suggestions are ranked by **actual user behaviour**, not by a third-party estimate. They tell you:

- 🔍 **What people actually type** — not what a keyword tool guesses
- 🏷️ **Long-tail phrases** you would never brainstorm on your own
- 📈 **Demand ranking** — `position` 1 is the strongest signal
- ⚡ **Fresh data** — pulled live at run time, not from a stale index

Typical users: game publishers, store-page optimizers and games-market analysts.

### How it works

For every seed keyword the Actor queries Steam's public suggestion endpoint. With **a–z expansion**
enabled (default) it also queries `seed a` … `seed z`, uncovering far more long-tail results than a single
lookup. Results are deduplicated and pushed to the dataset.

### Input

| Field | Type | Default | Description |
|---|---|---|---|
| `keywords` | array | — | Seed keywords, one per line |
| `expandAlphabet` | boolean | `true` | Also query "seed a" … "seed z" |
| `expandNumbers` | boolean | `false` | Also query "seed 0" … "seed 9" |
| `keepDuplicates` | boolean | `false` | Keep a suggestion found under several prefixes |
| `requestDelayMs` | integer | `120` | Politeness delay between requests |

### Output

One dataset item per suggestion:

```json
{
    "seed": "witcher",
    "query": "witcher r",
    "suggestion": "witcher reel wall mount",
    "position": 2,
    "collectedAt": "2026-08-05T09:00:00.000Z"
}
```

`position` is the rank in Steam's own list — 1 means the strongest demand signal for that query.

### What to expect

One seed with a–z expansion ≈ 27 queries. A batch of 10 seeds usually returns a few hundred to a few
thousand unique suggestions in under two minutes.

### FAQ

**Is this legal?** The Actor collects publicly available, non-personal suggestion data — the same
suggestions any visitor sees on Steam. No login, no personal data, no access controls bypassed.

**Do suggestions include search volume?** Steam does not expose volume. Use `position` as the
demand-rank signal, or combine with your favourite volume tool.

**Can I run it on a schedule?** Yes — use Apify Schedules to track how suggestions change over time.

**Can I export to CSV / Google Sheets?** Yes, from the run's Output tab or via the API.

# Actor input Schema

## `keywords` (type: `array`):

One or more seed keywords. Each is queried on Steam and (optionally) expanded with a–z / 0–9 prefixes to uncover long-tail suggestions.

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

Also query "seed a" … "seed z" (26 extra queries per seed). Recommended.

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

Also query "seed 0" … "seed 9" (10 extra queries per seed).

## `keepDuplicates` (type: `boolean`):

By default a suggestion found under several prefixes is stored once per seed.

## `requestDelayMs` (type: `integer`):

Politeness delay between calls.

## Actor input object example

```json
{
  "keywords": [
    "witcher"
  ],
  "expandAlphabet": true,
  "expandNumbers": false,
  "keepDuplicates": false,
  "requestDelayMs": 120
}
```

# Actor output Schema

## `suggestions` (type: `string`):

All collected suggestions with rank and seed keyword.

## `suggestionsCsv` (type: `string`):

The same suggestions as a spreadsheet-ready CSV file.

# 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 = {
    "keywords": [
        "witcher"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("emreyilmaz/steam-game-search-suggest").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 = { "keywords": ["witcher"] }

# Run the Actor and wait for it to finish
run = client.actor("emreyilmaz/steam-game-search-suggest").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 '{
  "keywords": [
    "witcher"
  ]
}' |
apify call emreyilmaz/steam-game-search-suggest --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=emreyilmaz/steam-game-search-suggest",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/39GuI4Ldlqr21nfpf/builds/l0SPPuQlYfBolIzaI/openapi.json