Google Analytics 4 MCP

ga4_get_metadata

Read-only

Retrieve the full GA4 dimension and metric catalog for a property, including custom fields when a property ID is supplied. Use it to discover valid field names before creating reports.

Instructions

Fetch the full GA4 dimension + metric catalog for a property.

If property_id is omitted, returns the universal catalog (excludes property-specific custom fields). Pass a property_id to include custom dimensions and metrics like 'customEvent:foo' and 'customUser:signup_plan'.

Response: {"dimensions": [...], "metrics": [...]}. Each entry has api_name, ui_name, description, category, custom_definition.

Call this before run_report when the agent is uncertain about field names: GA4's catalog is large and custom fields require the property to resolve.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "ga4_get_metadata"
  }
}

Input Schema

Name	Required	Description	Default
`property_id`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Sep 8, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Beyond the readOnlyHint annotation, the description explains the key behavioral difference between omitting and passing property_id, what kind of fields appear in each case, and the general response shape. This is exactly the information an agent needs to decide how to invoke the tool.

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?

The description is front-loaded with the core purpose, then gives parameter behavior, response shape, and usage guidance in a compact, efficient way. Every sentence adds value and no fluff is present.

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?

For a read-only metadata tool with one optional parameter and an output schema, the description covers the purpose, parameter semantics, response entry shape, and when to use it before running reports. Nothing essential is missing.

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

Parameters5/5

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

The input schema provides no description for property_id, and schema coverage is 0%. The description fully compensates by explaining that omitting it returns the universal catalog and passing it includes property-specific custom dimensions and metrics, with concrete examples.

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 states a specific verb and resource: 'Fetch the full GA4 dimension + metric catalog for a property.' It clearly differentiates itself from report tools and sibling list tools by emphasizing the full catalog, including custom fields when a property_id is supplied.

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 gives clear, actionable guidance: call this before run_report when uncertain about field names, and explains when to include property_id. It does not explicitly rule out alternatives like ga4_list_custom_dimensions, but the context is clear enough for an agent to select it appropriately.

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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