@applyra/mcp-server
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AlicenseAqualityBmaintenanceProvides App Store Optimization tools for AI agents, enabling app lookup, keyword research, ASO audit, review mining, and revenue estimation across iOS and Google Play.4381 npmMIT
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ASO Atlas MCP serverofficial
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TDQS
Scored across 25 tools
Each tool targets a distinct resource+action, and descriptions actively differentiate near-neighbors (e.g. get_keyword_rank_history vs get_app_score_history, check_metadata vs simulate_metadata, list vs get_metadata_simulation). The keyword-inspection pair (inspect_keyword vs list_keyword_inspections) is also cleanly split between analysis and history. No two tools appear to do the same thing.
Overwhelmingly consistent snake_case verb_noun pattern (add_competitor, list_applications, run_niche_analysis, get_aso_health), with a few related variants like track_keywords/untrack_keyword that still read clearly. The only real deviation is top_charts, which drops the verb prefix. Minor, but it breaks the otherwise uniform convention.
25 tools is on the heavy side, but the ASO domain is genuinely broad (apps, keywords, competitors, metadata auditing/simulation, niche analysis, top charts, account usage), and each tool maps to a distinct function with little redundancy. Slightly over what's ideal but defensible for the scope.
Coverage is strong: full add/list/remove for competitors, complete track/untrack/list/favorite for keywords, validate+simulate+retrieve lifecycle for metadata, and run/list for niche analyses and charts. The main gap is app lifecycle management—there is no remove_application or update_application, so a tracked app can be created but not edited or deleted.