# Steam Games Scraper - Prices, Reviews & Details (No API Key) (`flash_scraper/steam-games-scraper`) Actor

Scrape Steam games into a clean dataset: search by keyword, pass app IDs, or pull top sellers, new releases and specials. Get price, discount, genres, developer, publisher, release date, platforms, Metacritic, review score and recent reviews. Keyless public Steam API — no key, no proxy.

- **URL**: https://apify.com/flash\_scraper/steam-games-scraper.md
- **Developed by:** [Flash Scrape](https://apify.com/flash_scraper) (community)
- **Categories:** E-commerce, Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.50 / 1,000 games

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

## Steam Games Scraper — Prices, Discounts, Reviews & Details (No API Key)

Turn the **Steam store** into a clean, structured dataset. Search by keyword, hand it exact
app IDs, or pull a ready-made discovery list (top sellers, new releases, specials, coming
soon) — and get **one tidy row per game**: price, discount, genres, tags, developer,
publisher, release date, platforms, Metacritic score, review score + counts, and (optionally)
recent reviews.

Runs on Steam's **public storefront APIs** — **no API key, no login, no proxy**.

### What you can do with it

- 💸 **Price & discount monitoring** — track sale prices across a watchlist of games.
- 📊 **Market / competitor research** — pull top sellers or a genre and compare pricing, tags, and reviews.
- 💬 **Review-sentiment analysis** — grab review scores, positive %, and recent review texts.
- 🗂️ **Catalog building** — export a genre or search into a spreadsheet or JSON feed.

### Input

| Field | Type | Description |
|---|---|---|
| `searchTerms` | array | Keywords to search the Steam store (e.g. `Hades`, `roguelike`). |
| `appIds` | array | Exact Steam app IDs (from `store.steampowered.com/app/<APP_ID>`). |
| `discover` | select | `top_sellers` / `new_releases` / `specials` / `coming_soon` (or `none`). |
| `countryCode` | string | Region for pricing (Steam `cc`), e.g. `us`, `gb`, `de`. Default `us`. |
| `language` | string | Content language, e.g. `english`, `french`. Default `english`. |
| `includeReviews` | boolean | Attach a review summary (and optional review texts) to each game. |
| `maxReviewsPerGame` | integer | Recent reviews per game when reviews are on (0 = summary only). |
| `maxItems` | integer | Max games to return (1–200). |

You can combine inputs — e.g. a couple of `searchTerms` **plus** `discover: specials`.

#### Example

```json
{
  "searchTerms": ["Hades", "Stardew Valley"],
  "discover": "specials",
  "countryCode": "us",
  "includeReviews": true,
  "maxReviewsPerGame": 5,
  "maxItems": 25
}
```

### Output (one row per game)

`app_id`, `name`, `type`, `is_free`, `price_formatted`, `price_final_cents`,
`price_initial_cents`, `discount_percent`, `currency`, `on_sale`, `short_description`,
`developers`, `publishers`, `genres`, `categories`, `release_date`, `coming_soon`,
`windows` / `mac` / `linux`, `required_age`, `metacritic_score`, `recommendations_total`,
`header_image`, `steam_url`, `country`.

With `includeReviews`: `review_score_desc`, `total_reviews`, `total_positive`,
`total_negative`, `positive_pct`, and `reviews[]` (`voted_up`, `playtime_hours`, `review`,
`created_at`, `votes_up`).

### Notes

- Pricing reflects the `countryCode` you choose — Steam localizes prices per region.
- Some titles are region-locked or delisted and return no store data; those are skipped.
- Data comes from Steam's public endpoints; be reasonable with volume. The actor paces
  requests and retries automatically on rate limits.

# Actor input Schema

## `searchTerms` (type: `array`):

Keywords to search the Steam store, e.g. 'Hades', 'roguelike', 'Baldur's Gate'. Each term returns its best-matching games.

## `appIds` (type: `array`):

Exact Steam app IDs to fetch, e.g. 413150 (Stardew Valley), 1145360 (Hades). Found in a game's store URL: store.steampowered.com/app/\<APP\_ID>.

## `discover` (type: `string`):

Pull a ready-made list from the Steam storefront instead of (or in addition to) searching.

## `countryCode` (type: `string`):

Two-letter country code for pricing and availability (Steam 'cc' param), e.g. us, gb, de, ma, in.

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

Steam content language for names/descriptions, e.g. english, french, german, spanish.

## `includeReviews` (type: `boolean`):

Add a review summary (score, positive %, totals) to each game, and optionally recent review texts.

## `maxReviewsPerGame` (type: `integer`):

When 'Include reviews' is on, how many recent reviews to attach to each game (0 = summary only).

## `maxItems` (type: `integer`):

Maximum number of games to return across all inputs.

## Actor input object example

```json
{
  "searchTerms": [
    "Hades"
  ],
  "discover": "none",
  "countryCode": "us",
  "language": "english",
  "includeReviews": false,
  "maxReviewsPerGame": 10,
  "maxItems": 50
}
```

# 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 = {
    "searchTerms": [
        "Hades"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("flash_scraper/steam-games-scraper").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 = { "searchTerms": ["Hades"] }

# Run the Actor and wait for it to finish
run = client.actor("flash_scraper/steam-games-scraper").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 '{
  "searchTerms": [
    "Hades"
  ]
}' |
apify call flash_scraper/steam-games-scraper --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/MG9VC912cjRZlFF0j/builds/UCL1v8bocggoNUgde/openapi.json