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ga4-mcp

ga4-mcp

by onionst
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

ga4_overview

Retrieve daily Google Analytics 4 metrics including users, sessions, engagement, key events, and revenue for a property over a date range.

Instructions

Return daily users, sessions, engagement, key events, and revenue.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "property_id": "<property_id>"
    },
    "name": "ga4_overview"
  }
}

Input Schema

NameRequiredDescriptionDefault
end_dateNoyesterday
start_dateNo28daysAgo
property_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

C2.7/5.0
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. 'Return daily users...' indicates a read-only overview of aggregate metrics, which is some transparency, but it does not mention date handling, required property_id, or any caveats about the data returned.

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

Conciseness4/5

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

The description is a single, efficient sentence that gets straight to the point. It is appropriately short for a simple overview tool, though it could have added a little more context without losing conciseness.

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

Completeness2/5

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

The tool has three parameters, no annotations, and only a bare output list; an output schema exists, but it does not explain how parameters control the returned data. The description lacks enough context for an agent to confidently call this tool correctly for a specific request.

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

Parameters1/5

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

Schema description coverage is 0%, and the description does not compensate by explaining what property_id, start_date, or end_date mean or how they affect results. It only lists output metrics, leaving parameter semantics entirely to the schema's basic type/name hints.

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

Purpose4/5

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

The description specifies an action ('Return') and a concrete resource: daily users, sessions, engagement, key events, and revenue. It clearly conveys what the tool produces, though it does not explicitly distinguish itself from sibling tools like ga4_report or ga4_realtime.

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

Usage Guidelines2/5

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

There is no guidance about when to use this tool versus its siblings, nor any exclusions or alternatives mentioned. The description only states what it returns, so an agent must infer usage from the name and output list.

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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