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google-analytics-mcp

Get Property Metadata

get_property_metadata

Discover valid dimensions and metrics for a Google Analytics 4 property before running reports, ensuring your report queries use correct field names.

Instructions

List all valid dimensions and metrics available for a Google Analytics 4 property.

Use this before calling run_report to discover which metric and dimension names are valid for a specific property. Different properties may have custom dimensions and metrics in addition to the standard GA4 ones.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
property_idYesGoogle Analytics 4 property ID (numeric, e.g., "123456789")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

No annotations are provided, so the description must cover behavioral context. It discloses that the tool returns a list of valid dimensions/metrics and notes that output may vary by property due to custom entries. While it doesn't explicitly state 'read-only', the context strongly implies it, and the output schema handles return format. This is adequate but not exhaustive.

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 sentences with no redundancy. The purpose is stated first, followed by usage context. Every word earns its place.

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 simple metadata discovery tool with a single parameter and an output schema, the description is complete. It covers the essential use case, mentions property-specific variations, and directs the agent to the appropriate next step.

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?

The schema description covers property_id completely (100% coverage), and the tool description adds no additional parameter-level meaning. Baseline of 3 applies because the schema already documents the parameter adequately.

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 ('List') and resource ('valid dimensions and metrics for a GA4 property'), clearly distinguishing this from the sibling reporting tools like run_report and get_page_views. It leaves no ambiguity about what the tool does.

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

Usage Guidelines5/5

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

It explicitly instructs the agent to use this tool before calling run_report to discover valid names, and notes that custom dimensions/metrics may vary per property. This gives clear when-to-use guidance and implies it is a discovery step, not a data retrieval step.

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