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Glama

Google_analytics

by io.github.pipeworx-io

Ga Get Metadata

ga_get_metadata
Read-onlyIdempotent

Discover available dimensions and metrics for a GA4 property. Returns field names, descriptions, and data types to build accurate ga_run_report queries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
property_idYesGA4 property ID (numeric)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoAPI response kind identifier
errorNoError code if connection not established
messageNoError message if connection not established
metricsNoAvailable metrics for this GA4 property
dimensionsNoAvailable dimensions for this GA4 property

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed14 schema fields changed
    • changedOutput schema / properties / dimensions / description
      Previous value: -"Available dimensions for this property"New value: +"Available dimensions for this GA4 property"
    • changedOutput schema / properties / dimensions / items / properties / dataType / description
      Previous value: -"Data type of the dimension"New value: +"Data type (STRING, INT64, etc.)"
    • addedOutput schema / properties / dimensions / items / properties / deprecatedApiNames
      Added value: +{
+  "description": "Deprecated API names for this dimension",
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}
    • changedOutput schema / properties / dimensions / items / properties / description / description
      Previous value: -"Description of the dimension"New value: +"Human-readable description"
    • removedOutput schema / properties / dimensions / items / properties / uiName
      Removed value: -{
-  "description": "UI display name",
-  "type": "string"
-}
    • changedOutput schema / properties / error / description
      Previous value: -"Error message if connection failed"New value: +"Error code if connection not established"
    • addedOutput schema / properties / kind
      Added value: +{
+  "description": "API response kind identifier",
+  "type": "string"
+}
    • changedOutput schema / properties / message / description
      Previous value: -"Error details if connection failed"New value: +"Error message if connection not established"
    • changedOutput schema / properties / metrics / description
      Previous value: -"Available metrics for this property"New value: +"Available metrics for this GA4 property"
    • removedOutput schema / properties / metrics / items / properties / dataType
      Removed value: -{
-  "description": "Data type of the metric",
-  "type": "string"
-}
    • addedOutput schema / properties / metrics / items / properties / deprecatedApiNames
      Added value: +{
+  "description": "Deprecated API names for this metric",
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}
    • changedOutput schema / properties / metrics / items / properties / description / description
      Previous value: -"Description of the metric"New value: +"Human-readable description"
    • addedOutput schema / properties / metrics / items / properties / type
      Added value: +{
+  "description": "Metric type (CURRENCY, TIME_MSEC, etc.)",
+  "type": "string"
+}
    • removedOutput schema / properties / metrics / items / properties / uiName
      Removed value: -{
-  "description": "UI display name",
-  "type": "string"
-}
  2. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "dimensions": {
+      "description": "Available dimensions for this property",
+      "items": {
+        "properties": {
+          "apiName": {
+            "description": "API name of the dimension",
+            "type": "string"
+          },
+          "dataType": {
+            "description": "Data type of the dimension",
+            "type": "string"
+          },
+          "description": {
+            "description": "Description of the dimension",
+            "type": "string"
+          },
+          "uiName": {
+            "description": "UI display name",
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "error": {
+      "description": "Error message if connection failed",
+      "type": "string"
+    },
+    "message": {
+      "description": "Error details if connection failed",
+      "type": "string"
+    },
+    "metrics": {
+      "description": "Available metrics for this property",
+      "items": {
+        "properties": {
+          "apiName": {
+            "description": "API name of the metric",
+            "type": "string"
+          },
+          "dataType": {
+            "description": "Data type of the metric",
+            "type": "string"
+          },
+          "description": {
+            "description": "Description of the metric",
+            "type": "string"
+          },
+          "uiName": {
+            "description": "UI display name",
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "type": "object"
+}
  3. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "property_id": "123456789"
+  }
+]
  4. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive. The description adds that it returns field names, descriptions, data types, which is useful output behavior. It doesn't contradict annotations and adds context beyond the safety profile.

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?

Two tight sentences, no waste, front-loaded with action and resource.

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

Completeness5/5

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

Given the single parameter, safe operation, and presence of an output schema, the description covers the tool's purpose and output sufficiently. It could mention the returned format is a list but the schema covers that. Complete enough for a simple metadata lookup.

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?

Only one parameter, property_id, is fully documented in the schema (100% coverage). The description reinforces that this is a GA4 property but doesn't add additional semantics or format constraints beyond 'numeric'.

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 ('Discover') and identifies the resource ('available dimensions and metrics for a GA4 property'), and explicitly ties it to building accurate ga_run_report queries, distinguishing it from report execution tools.

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?

It clearly states the context for use: before querying reports, to get accurate fields. It implies when to use (when needing valid dimensions/metrics) and points to ga_run_report as the downstream consumer. It doesn't explicitly mention alternatives or when-not-to-use, but context is clear.

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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TDQS

A3.5/5.0
Disambiguation2/5

Several tools overlap heavily: ask_pipeworx and ask_pipeworx_beta are explicitly identical, ask_pipeworx_grounded and deep_research both route queries to the same 5,529 tools, and ai_visibility_check vs scan_competitor_ai_presence are near-duplicates. Only the small ga_* subset is clearly distinct.

Naming Consistency2/5

Conventions are mixed: GA tools use a ga_ prefix, but the majority use arbitrary names like ask_pipeworx, deep_research, remember, scan_dependency, and polymarket_arbitrage. No consistent verb_noun pattern across the set.

Tool Count2/5

35 tools is heavy, and the vast majority (31) are unrelated Pipeworx utilities rather than Google Analytics functionality. Only 4 tools actually serve the stated GA purpose, making the count inappropriate for the server name.

Completeness2/5

For Google Analytics, the surface is minimal: list properties, metadata, realtime, and run report—no property management, user management, or data mutation. As a Pipeworx toolkit it's broad but lacks full lifecycle coverage for any single domain.

Resources