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google-data-mcp

by ducnhd
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Python
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    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A4/5.0

    Scored across 7 tools

    Disambiguation5/5

    Each tool targets a distinct Google service or distinct operation within a service. google_trends_compare and google_trends_interest are clearly differentiated by their normalization semantics, and the ad tools (advertisers vs creatives) have distinct purposes. No two tools could be easily confused.

    Naming Consistency4/5

    Tool names follow a consistent service-prefix pattern (google_trends_, google_ads_, youtube_, google_play_), but the second part mixes nouns, verbs, and gerunds (e.g., compare, trending, listing, advertisers, creatives, reviews). While not perfectly uniform, the pattern is predictable and readable.

    Tool Count5/5

    With 7 tools, the set is well-scoped. It covers multiple Google data services without bloating, and each tool addresses a common use case, making the count feel right for the stated purpose.

    Completeness4/5

    The tool surface covers core workflows for Trends (compare, trending, interest), Ads (advertiser search and creatives), YouTube (listing videos), and Play (reviews). Minor gaps exist (e.g., no YouTube channel details, no Play app metadata), but the essential read operations are present. The server explicitly notes limitations like no transcripts, which clarifies its boundaries.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues

    Resources