@applyra/mcp-server
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AlicenseAqualityBmaintenanceScans websites to evaluate agent-readiness and produce an ASO Score Report across 34 signals, helping improve discoverability, trust, and interoperability for AI agents.5437 npm2MIT
@sonarapp/mcpofficial
AlicenseAqualityCmaintenanceProvides App Store Optimization tools for AI agents, enabling app lookup, keyword research, ASO audit, review mining, and revenue estimation across iOS and Google Play.43123 npmMIT
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TDQS
Scored across 30 tools
Most tools map to a distinct resource and action, and closely related pairs such as inspect_keyword vs list_keyword_inspections and check_metadata vs simulate_metadata are separated by explicit workflow descriptions. A few pairs still require careful reading, but the boundaries are generally clear.
All tool names use snake_case and mostly follow a verb_noun pattern. Minor deviations such as top_charts and the track/untrack pair are still readable and predictable.
Thirty tools is heavy, but the server spans several ASO subdomains: apps, keywords, competitors, notes, metadata, charts, research, and account usage. The count is on the upper end, yet each tool maps to a distinct operation rather than obvious bloat.
Core ASO workflows are well covered: app tracking, keyword research and tracking, rank history, competitor tracking, notes, metadata validation and simulation, health audits, top charts, and account usage. Gaps include no app removal/update or single-app retrieval, and competitor update is absent, but these are minor workarounds.