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    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables querying Google Analytics data via natural language, providing tools for account and property insights, core reports, funnels, realtime reports, and custom dimensions/metrics.
      Apache 2.0
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI assistants like Claude, ChatGPT, and Cursor to query GA4 traffic, conversion, channel, e-commerce, and demographic reports conversationally, and to manage properties, data streams, audiences, key events, and other configuration through 62 read and write actions. Access can be scoped per account with read-only mode and destructive actions disabled by default.
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables querying Google Analytics 4 in plain language after signing in with a Google account through OAuth, so every account and property the user can already access is visible without per-property service-account setup. Provides read-only tools to list properties, inspect metadata, run and compare reports, track AI-assistant referrals, and view realtime data.
      MIT
    • A
      license
      A
      quality
      A
      maintenance
      Enables read-only access to Google Analytics 4 data through seventeen tools covering reports, realtime data, funnels, pivots, metadata, and admin lists. It runs locally with service account credentials and lets users query properties via standard MCP clients.
      17
      32 PyPI
      MIT
    • F
      license
      A
      quality
      D
      maintenance
      Enables interaction with Google Analytics 4 to manage accounts, run standard or realtime reports, and validate event parameters. It supports dual authentication methods and integrates with GTM for end-to-end data collection orchestration.
      8
      -

    TDQS

    A3.6/5.0

    Scored across 36 tools

    Disambiguation4/5

    Most tools target clearly distinct GA4 surfaces (top events vs. realtime vs. pivot vs. batch reports; custom dimensions vs. custom metrics; list vs. create dimension). A few pairs are genuinely close — ga4_top_events vs. ga4_event_counts, ga4_funnel vs. ga4_step_conversion, ga4_check_access vs. ga4_test_connection, and the three Firebase tools (property_from_firebase / firebase_apps / firebase_links) — but the descriptions explicitly cross-reference and differentiate them, which mitigates the risk.

    Naming Consistency4/5

    All 36 tools share a uniform ga4_ prefix and snake_case, so the family is immediately recognizable. Most names are noun-phrase report/resource names (ga4_active_users, ga4_audiences, ga4_data_streams) while a handful use verb_noun (ga4_create_custom_dimension, ga4_list_properties, ga4_run_report, ga4_configure); the mix is readable but not a single strict verb_noun pattern.

    Tool Count3/5

    36 tools is heavy for one server and well past the comfortable 3-15 range, partly because many convenience wrappers (top_events, event_counts, active_users, acquisition, tech_breakdown, screen_views, cohort_retention, compare_periods, step_conversion) are thin specializations of ga4_run_report. The breadth of GA4 Data + Admin + Firebase + connection-management domains justifies a large surface, but consolidation would make selection easier.

    Completeness4/5

    Reporting coverage is excellent — generic, batch, pivot, realtime, funnel, cohort, and many prebuilt reports — and admin read coverage spans properties, streams, audiences, key events, links, retention, and change history. The main gap is write/CRUD depth: only custom dimension creation exists, with no update/delete of dimensions, key events, or streams, though connection setup, access diagnostics, and metadata discovery are all present.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues