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surendranb

Google Analytics MCP Server

by surendranb

get_metrics_by_category

Read-onlyIdempotent

Retrieve all metrics in a specific category by providing the exact category name. Returns each metric's API name and description to help you locate available metrics for your GA4 queries.

Instructions

Return all metrics in a specific category with their API names and descriptions.

Returns: {"metric_api_name": "description", ...}

The category name must exactly match a value returned by list_metric_categories. Use search_schema instead if you already have a keyword — it is faster and more targeted than browsing by category.

Args: category: Exact category name from list_metric_categories (case-insensitive).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryYes
Install Server

TDQS

A4.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint true, and the description adds return format context without contradicting annotations. It doesn't mention side effects, but read-only is implied and covered.

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?

Concise and well-structured: clear purpose, return format, usage note, and parameter explanation are all included without redundancy.

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?

Despite lacking an output schema, the description explicitly states the return format (dictionary mapping). It also provides source for category names and differentiates from alternative tools, covering all necessary context.

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 schema only specifies type string, but the description adds crucial semantics: it must be an exact category name from list_metric_categories and is case-insensitive, fully clarifying the parameter's meaning.

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?

States clearly that it returns all metrics in a specific category with API names and descriptions, and distinguishes from sibling tools like search_schema and get_dimensions_by_category.

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?

Provides explicit prerequisite (category must exactly match list_metric_categories) and recommends search_schema as a faster alternative for keyword searches, offering clear when-to-use guidance.

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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