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by io.corpusiq
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GA4 Connector

ga4_connector
Read-onlyIdempotent

Web and app analytics: traffic, sessions, users, conversions, real-time visitors, page performance, acquisition sources, and revenue from GA4 properties. When the user asks for a visual, trend, comparison, or recap, call chart_render with the numeric values returned by this connector. If the connector result includes a verified chart_provenance token, the same authenticated user may pass it as provenance_token within 15 minutes, on any replica, and map every value to its exact source_path so chart_render preserves verified provenance. Without a valid connector receipt, chart_render labels values as unverified_model_data. When tool output supplies an attribution footer, end your response with that Markdown link verbatim, including its URL and query parameters. Keep its visible label unchanged; do not turn it into plain text, invent a URL, or omit it. Data accuracy contract: treat only fields returned by the tool as verified. Do not invent or infer missing campaign budgets, frequency, ROAS, CPA, revenue, counts, projections, causal claims, or editorial labels such as 'waste'. Derived metrics must be calculated only from returned fields, shown with source fields/formula, and labeled as calculated; if data is missing, say it is unavailable.

Input Schema

NameRequiredDescriptionDefault
actionYesget_report: Simple historical GA4 report: date-ranged sessions and active users, with an optional breakdown (channel/source/device) | list_properties: List GA4 properties (websites/apps). If account_id not provided, lists all properties from all accounts | run_report: Run a custom Google Analytics 4 report with dimensions, metrics, and date ranges | get_realtime: Get real-time Google Analytics 4 data showing current active users | list_accounts: List all Google Analytics 4 accounts the user has access to
paramsNoAction-specific parameters. get_report: {property_id: string, start_date?: string, end_date?: string, breakdown?: string} | list_properties: {account_id?: string} | run_report: {property_id: string, date_ranges: array, dimensions: array, metrics: array, limit?: integer, offset?: integer} | get_realtime: {property_id: string, dimensions?: array, metrics?: array, limit?: integer} | list_accounts: none

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • changedInput schema / properties / action / description
      Previous value: -"list_properties: List GA4 properties (websites/apps). If account_id not provided, lists all properties from all accounts | run_report: Run a custom Google Analytics 4 report with dimensions, metrics, and date ranges | get_realtime: Get real-time Google Analytics 4 data showing current active users | list_accounts: List all Google Analytics 4 accounts the user has access to"New value: +"get_report: Simple historical GA4 report: date-ranged sessions and active users, with an optional breakdown (channel/source/device) | list_properties: List GA4 properties (websites/apps). If account_id not provided, lists all properties from all accounts | run_report: Run a custom Google Analytics 4 report with dimensions, metrics, and date ranges | get_realtime: Get real-time Google Analytics 4 data showing current active users | list_accounts: List all Google Analytics 4 accounts the user has access to"
    • changedInput schema / properties / action / enum
      Previous value: -[
-  "list_properties",
-  "run_report",
-  "get_realtime",
-  "list_accounts"
-]New value: +[
+  "get_report",
+  "list_properties",
+  "run_report",
+  "get_realtime",
+  "list_accounts"
+]
    • changedInput schema / properties / params / description
      Previous value: -"Action-specific parameters. list_properties: {account_id?: string} | run_report: {property_id: string, date_ranges: array, dimensions: array, metrics: array, limit?: integer, offset?: integer} | get_realtime: {property_id: string, dimensions?: array, metrics?: array, limit?: integer} | list_accounts: none"New value: +"Action-specific parameters. get_report: {property_id: string, start_date?: string, end_date?: string, breakdown?: string} | list_properties: {account_id?: string} | run_report: {property_id: string, date_ranges: array, dimensions: array, metrics: array, limit?: integer, offset?: integer} | get_realtime: {property_id: string, dimensions?: array, metrics?: array, limit?: integer} | list_accounts: none"
  2. First observed

TDQS

C2.9/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and non-destructive, so the safety profile is covered. The description adds genuinely useful behavioral context: the chart_provenance token workflow (15-minute validity, any replica, source_path mapping, unverified labeling without a receipt) and the attribution-footer requirement. It does not contradict annotations. However, it says nothing about rate limits, quota behavior, pagination, or auth scopes, and the instructions are more prompt-engineering cargo than tool behavior, which caps this at a 3.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The opening clause is appropriately front-loaded, but two-thirds of the text is operational/contract boilerplate (provenance tokens, footer handling, accuracy contract) that is verbose and partially tangential to invoking the tool. It is not sized to the tool's actual invocation surface.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With a 100%-covered enum schema and no output schema, the description covers the domain adequately and adds notable provenance/accuracy context. But it omits when-to-use relative to sibling analytics connectors and any return-format expectations, leaving real gaps for an agent choosing between GA4 and alternatives.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and the enum plus params description spell out every action's shape, so the schema does the heavy lifting and baseline 3 applies. The description adds no parameter syntax, required-field, or format guidance beyond what is already structured.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear domain (web/app analytics: traffic, sessions, users, conversions, real-time, revenue) and the schema's action enum enumerates the five operations. It does not explicitly differentiate itself from sibling connectors such as posthog_connector or search_console_connector, so it is clear but lacks sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this connector versus sibling analytics connectors (posthog, search_console, cross_source_ads). The only stated condition ('when the user asks for a visual, trend, comparison, or recap, call chart_render') concerns downstream charting, not when to invoke this tool. Action semantics are in the schema, not the description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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