Steam MCP Server
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- AlicenseAqualityDmaintenanceIntegrates with Steam Web API to enable querying user profiles, game libraries, store data, and community features like reviews and workshop items.16MIT
- AlicenseAqualityCmaintenanceEnables AI assistants to query Steam profiles, libraries, achievements, store data, and reviews via the Steam Web API.152MIT
- AlicenseBqualityDmaintenanceProvides tools for interacting with the Steam Web API to access player profiles, game libraries, achievements, statistics, inventories, and game information through natural language.3458 npm5MIT
- AlicenseNot gradedqualityCmaintenanceProvides Steam Web API integration for querying owned games, player achievements, app news, and store details. Part of the Pipeworx MCP gateway enabling natural language queries to Steam data.297 npmMIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to recommend Steam games from natural language by searching games, finding similar titles, filtering by tags and platform, and retrieving detailed game metadata.1MIT
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TDQS
Scored across 26 tools
There are real clusters of overlapping tools (get_prices/get_items/discover_games/get_specials/get_featured; get_owned_games/get_recently_played/compare_players; the three achievement tools; get_reviews/get_review_histogram), but nearly every description explicitly says when to use a sibling instead, and states the key gating (key vs keyless, batch limits, full-library vs capped). An agent can resolve almost every choice from the descriptions alone; a couple of store/catalog boundaries (get_featured vs get_specials vs discover_games) still take careful reading.
All 26 tools use snake_case verb_noun form with domain-appropriate verbs (get_, search_, discover_, compare_, find_, resolve_). No camelCase or vague verb-only names; get_friend_list is the only minor noun-phrase deviation and still follows get_<resource>.
At 26 tools the surface is heavy, exceeding the typical 3-15 sweet spot and crossing the 25+ threshold. The breadth is genuinely earned by a wide domain (store catalog, deals, library, wishlist, friends, achievements, reviews, profiles), but a few clusters (get_prices vs get_items, get_specials vs get_featured vs discover_games) could be consolidated.
Coverage is strong for a read-only Steam surface: search, details, prices/items, discovery, deals, charts, library, wishlist, follows, friends, achievements (catalog/global/player), reviews and histograms, news, players, bans and vanity resolution. Minor gaps remain (no bundle/package or market/workshop lookups, no similar-games endpoint beyond tag-based discovery), but these are workarounds rather than dead ends.