google-analytics-mcp-server

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ga4 get bigquery export diagnostics

ga4_get_bigquery_export_diagnostics

Read-onlyIdempotent

Detect GA4 BigQuery export links and diagnose export modes, stream coverage, excluded events, and dataset location for a property.

Instructions

Detect GA4 BigQuery export links and diagnose export modes, stream coverage, excluded events, and dataset location.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`propertyId`	Yes	GA4 property ID (numeric, e.g., 123456789)
`includeDataStreams`	No	Include data stream summaries to compare against BigQuery exportStreams

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes	Original tool result: parsed JSON when the text is JSON, otherwise the text or multiple MCP content blocks. Provider fields depend on the selected query.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv2.0.0Sep 30, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "result": {
+      "anyOf": [
+        {
+          "additionalProperties": true,
+          "properties": {},
+          "type": "object"
+        },
+        {
+          "items": {},
+          "type": "array"
+        },
+        {
+          "type": "string"
+        },
+        {
+          "type": "number"
+        },
+        {
+          "type": "boolean"
+        },
+        {
+          "type": "null"
+        }
+      ],
+      "description": "Original tool result: parsed JSON when the text is JSON, otherwise the text or multiple MCP content blocks. Provider fields depend on the selected query."
+    }
+  },
+  "required": [
+    "result"
+  ],
+  "type": "object"
+}

First observedv1.0.0Aug 29, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already signal readOnly, idempotent, and non-destructive behavior. The description adds context beyond annotations by specifying exactly what is examined: export modes, stream coverage, excluded events, and dataset location. It does not disclose potential edge cases like empty results, but the output schema likely covers return specifics.

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

Conciseness5/5

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

A single dense sentence conveys the tool's purpose and diagnostic scope with no filler. Each listed item adds useful information, and the primary verb 'Detect' is front-loaded.

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

Completeness4/5

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

With an output schema present, read-only annotations, and a required propertyId documented in the input schema, the description is largely sufficient. It could be slightly more complete by mentioning when to prefer this tool over related diagnostics, but that gap is minor given the tool name and sibling context.

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?

Both parameters are fully described in the schema (propertyId and includeDataStreams), so the schema carries the semantic burden. The description does not add parameter-specific guidance, only implicitly connects 'stream coverage' to includeDataStreams. Baseline 3 is appropriate given 100% schema description coverage.

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

Purpose5/5

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

The description uses a specific verb ('Detect'/'diagnose') with a concrete resource (GA4 BigQuery export links) and enumerates diagnostic dimensions: export modes, stream coverage, excluded events, and dataset location. This clearly distinguishes it from sibling diagnostic tools like ga4_get_audience_export_diagnostics or ga4_get_ecommerce_diagnostics.

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

Usage Guidelines4/5

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

The description makes the tool's domain clear: BigQuery export diagnostics. An agent can infer when to choose this over related diagnostic tools, though it does not explicitly name alternatives or state when not to use it. This is clear context but lacks explicit exclusions.

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