mcp-server-steam-backlog
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- 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.-
- AlicenseNot gradedqualityBmaintenanceEnables AI assistants to query and manage a unified multi-platform game library, including playtime, achievements, ratings, backlog status, recommendations, duplicate reconciliation, and genre enrichment through MCP tools.MIT
- AlicenseAqualityBmaintenanceExposes Steam Web API tools as MCP resources for Claude Code, Claude Desktop, and Gemini CLI, enabling profile lookups, game searches, achievement tracking, and more.1125 npm1MIT
- AlicenseAqualityDmaintenanceConnects Claude to your Steam library via the Steam Web API. Query your games, playtime, recently played history, and store metadata using natural language. Zero-config install via npx steam-mcp.525 npm6MIT
- AlicenseAqualityDmaintenanceA local MCP server that lets Claude fetch data from your Steam game library via the Steam Web API. All tools are read-only.5Apache 2.0
- AlicenseAqualityDmaintenanceAn MCP server that connects AI assistants to the Steam Web API and storefront, enabling game library analysis, mood-based backlog recommendations, wishlist evaluation, and storefront searches.818 npmMIT
TDQS
Scored across 10 tools
Each tool targets a distinct resource+action: search (find_games), single-game detail (get_game), summary (get_overview), recommendation (suggest_picks), queue read vs. reorder, note write, lane write, and export start vs. status. The descriptions explicitly cross-reference each other (e.g. find_games says to use suggest_picks for recommendations), eliminating the main potential overlap.
All ten tools share the backlog_ prefix and follow a consistent snake_case verb_noun pattern (find_games, get_game, set_lane, reorder_next, start_export). No mixed conventions or vague verbs.
Ten tools is well within the ideal 3-15 range and each maps to a clear, non-redundant capability for a backlog dashboard: read, filter, recommend, triage, annotate, order, and refresh. Nothing feels padded or missing a counterpart.
The lifecycle is well covered: overview, filtered search, per-game detail, ranked picks, lane transitions, note management (including clearing), queue ordering, and export start/status. Minor gaps exist (no dedicated lane-listing beyond filter-by-lane in find_games, no batch note operations), but agents can work around them.