steam-mcp
Related Servers
Alternatives to steam-mcp
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityBmaintenanceA read-only MCP server that enables AI assistants to access a user's Steam library, playtime, achievements, friends, wishlist, and store data for backlog analysis, game recommendations, discount monitoring, and play-activity summaries.-
- AlicenseAqualityBmaintenanceMCP server enabling AI assistants to search Steam games, retrieve official store metadata, and analyze player review sentiment via public Steam Storefront JSON APIs without an API key.311MIT
- AlicenseAqualityBmaintenanceAn MCP server that exposes your Steam, Epic Games Store, and IGDB game data as tools, enabling game library queries, install status checks, and metadata enrichment.122MIT
- AlicenseAqualityCmaintenanceMCP server for Steam that enables LLM agents to manage gaming libraries, achievements, stats, and discover store content through 20 tools.212MIT
- AlicenseCqualityDmaintenanceA feature-rich Model Context Protocol server that gives AI assistants full access to your Steam game library.14296MIT
- AlicenseAqualityBmaintenanceAn MCP server for Backloggd, the video game tracker. It lets an AI assistant search the game catalogue and read and manage your library — statuses, ratings, logs, play sessions, reviews and lists — as the signed-in you.45MIT
TDQS
Scored across 8 tools
Each tool targets a distinct resource and action: recently played, library, wishlist, app details, reviews, title search, library recommendations, and new discoveries. No two tools overlap in purpose, making selection unambiguous.
All tools follow a clear verb_noun or verb_preposition_noun pattern (get_recently_played, get_library, search_games, recommend_from_library, discover_games). The naming style is consistent throughout.
8 tools is well-scoped for a Steam discovery server. Each tool addresses a core need (library, wishlist, metadata, reviews, search, recommendations) without redundancy or bloat.
The tool set covers the primary discovery and recommendation workflows: assessing user preferences, evaluating specific games, and finding new titles. Minor gaps exist (e.g., no direct wishlist management or similar-game lookup), but these are not critical dead ends.