Steam MCP Server — Game Search & Deals for AI

🧠 MCP Server — AI Agent Ready

This actor is a Model Context Protocol (MCP) server — AI assistants (Claude, GPT, Cursor) can call it directly to search and extract data:

{"searchQuery": "example", "maxResults": 5}

Search Steam games, prices, and deals. Returns titles, prices, ratings, discounts — perfect for gaming market intelligence.

Search and extract game data from Steam Store with full API enrichment. Extract titles, prices, ratings, genres, tags, descriptions, screenshots, and 27+ fields per game.

Features

• Search & Extract — Search Steam Store by keyword and extract game listings from search results
• API Enrichment — Enrich every result with Steam's official API for detailed descriptions, tags, genres, screenshots, developers, publishers, and more
• Country-Specific Pricing — Pass a country code (cc) to get localized pricing (USD, EUR, GBP, etc.)
• Structured Output — All results normalized to a consistent schema with 27+ fields
• Lightweight — CheerioCrawler, fast and cost-effective (no Playwright)

Input Parameters

Parameter	Type	Default	Description
searchQuery	string	"cyberpunk"	Search term for Steam Store search
tags	string[]	[]	Steam tags to filter by (e.g. "Singleplayer", "RPG")
categories	string[]	[]	Steam categories (e.g. "Genre:Action", "Feature:Controller")
priceMin	number	0	Minimum price filter (0 = no minimum)
priceMax	number	0	Maximum price filter (0 = no maximum)
maxResults	number	0	Maximum number of games to extract (0 = no limit)
fetchDetails	boolean	true	Enrich results via Steam API (descriptions, tags, screenshots)
cc	string	"us"	Country code for localized pricing (e.g., us, de, gb, jp)
sortBy	string	"relevance"	Sort: relevance, price_asc, price_desc, name_asc, name_desc, released_desc
sortOrder	string	"desc"	Sort order: asc or desc

Output Schema

Each result contains the following fields:

Field	Type	Description
title	string	Game title
app_id	number	Steam App ID
type	string	App type (game, demorequire, etc.)
price_cents	number	Current price in cents
discount_percent	number	Current discount percentage
release_date	string	Release date (coming soon / month/year or exact date)
review_percentage	number	Positive review percentage (0-100)
review_sentiment	string	"Overwhelmingly Positive", "Very Positive", etc.
platforms	object	{ windows, mac, linux } — boolean flags
url	string	Steam Store URL
steam_url	string	Full Steam Store URL
source	string	Always "steam"
cc	string	Country code used for pricing
search_query	string	Original search query
short_description	string	Brief game description (from API)
detailed_description	string	Full HTML description (from API)
about_the_game	string	About section (from API)
header_image	string	Header image URL (from API)
capsule_image	string	Capsule image URL (from API)
website	string	Official game website (from API)
developers	array	Developer names
publishers	array	Publisher names
currency	string	Currency code (USD, EUR, etc.)
price_initial_cents	number	Original price before discount
price_final_cents	number	Current price after discount
is_free	boolean	Whether the game is free-to-play
required_age	number	Required age restriction
metacritic_score	number	Metacritic score (if available)
recommendations	number	Total number of user recommendations
genres	array	Genre names (e.g., "Action", "RPG")
tags	array	Tag names with counts
categories	array	Category names (e.g., "Single-player", "Steam Achievements")
screenshots	array	Screenshot image URLs (from API)
achievements_total	number	Total achievements (if available)
dlc_count	number	Number of DLC packages
supported_languages	array	Supported language codes

Example

Input

{
  "searchQuery": "rpg",
  "maxResults": 20,
  "fetchDetails": true,
  "cc": "US"
}

Output (per item)

{
  "title": "Baldur's Gate 3",
  "app_id": 1086940,
  "type": "game",
  "price_cents": 5999,
  "discount_percent": 0,
  "release_date": "3 Aug, 2023",
  "review_percentage": 96,
  "review_sentiment": "Overwhelmingly Positive",
  "platforms": { "windows": true, "mac": true, "linux": false },
  "url": "https://store.steampowered.com/app/1086940/Baldurs_Gate_3/",
  "steam_url": "https://store.steampowered.com/app/1086940/",
  "source": "steam",
  "cc": "US",
  "search_query": "rpg",
  "short_description": "Gather your party and return to the Forgotten Realms...",
  "developers": ["Larian Studios"],
  "publishers": ["Larian Studios"],
  "currency": "USD",
  "is_free": false,
  "genres": ["RPG", "Strategy"],
  "tags": ["RPG", "Story Rich", "Character Customization", ...],
  "categories": ["Single-player", "Multi-player", "Steam Achievements", ...],
  "screenshots": ["https://cdn.akamai.steamstatic.com/.../1.jpg", ...],
  "achievements_total": 54,
  "dlc_count": 0
}

Use Cases

• Game market research — Analyze pricing, genres, and tags across Steam's catalog
• Competitive analysis — Track competitor game details, pricing changes, and review trends
• Price monitoring — Set up recurring runs to detect sales and discount patterns
• Content aggregation — Build game recommendation engines or curated lists
• Data science — Train ML models on game metadata, pricing, and review correlations

Limitations

• Steam API allows only one App ID per request — enrichment is sequential (concurrency-limited)
• Free plan users: enrichment for 100+ games may take 30-60 seconds
• Steam rate limits apply — very large extractions (500+ games) may be throttled
• Some fields may be null for upcoming games or early access titles

Pricing

This actor uses Apify's Pay Per Event model:

• Result: $0.001 per result ($1.00 per 1,000 results)
• Actor Start: $0.00005 (one-time per run)

With CheerioCrawler, runs are extremely cost-effective — a search returning 20 enriched games costs just ~$0.025.

💬 Quick Start for AI Assistants

Copy and paste this into ChatGPT, Claude, or another AI assistant to get help using this actor:

---

You are helping me use the "Steam Store Scraper" on Apify (actor ID: twcEXldXp9Z44wDcG). It searches and extracts game data from Steam Store with full API enrichment — titles, prices, ratings, genres, tags, descriptions, screenshots, and 27+ fields per game.

Input fields:

• searchQuery: string, e.g. "cyberpunk" or "rpg" (default: "cyberpunk")
• tags: string array, Steam tags to filter (e.g. "Singleplayer", "RPG")
• categories: string array, Steam categories (e.g. "Genre:Action")
• priceMin, priceMax: number, price filter (0 = no limit)
• maxResults: number, max games (0 = no limit, default: 0)
• fetchDetails: boolean, enrich via Steam API (default: true)
• cc: string, country code for pricing (us, de, gb, jp, etc., default: "us")
• sortBy: string, "relevance" | "price_asc" | "price_desc" | "name_asc" | "released_desc"

Output fields: title, app_id, price_cents, discount_percent, review_percentage, platforms, url, genres, tags, developers, publishers, screenshots, 27+ total fields.

Help me with the right input, output processing, or troubleshooting.

Changelog

Version	Date	Changes
0.2	2026-07-17	Cloud deployment verified — 10 games, 10/10 enriched
0.1	2026-07-17	Initial release: search + Steam API enrichment, 27+ fields

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