flin-ga4-mcp

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get_summary

Read-onlyIdempotent

Reads aggregate Google Analytics 4 metrics, including users, sessions, engagement, page views, events, key events, and revenue, for a specified date range and optional account or property.

Instructions

Read aggregate users, sessions, engagement, page views, events, 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": {
      "start_date": "<start_date>",
      "end_date": "<end_date>"
    },
    "name": "get_summary"
  }
}

Input Schema

Name	Required	Description	Default
`account`	No
`end_date`	Yes
`start_date`	Yes
`property_id`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Oct 31, 2026

TDQS

C2.7/5.0

Behavior3/5

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

Annotations already cover the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false, openWorldHint=true), so the description only needs to add context. It adds the metric categories that constitute the response, but says nothing about date-range behavior, defaults for account/property_id, quota limits, or how aggregation granularity works.

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?

A single front-loaded sentence with no filler. It is efficient, though it spends its entire budget enumerating metrics rather than addressing the more consequential ambiguity around parameters.

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 presence of an output schema relieves the description of explaining return values, but with 0% schema description coverage on 4 parameters (including ambiguous account vs property_id scoping) and no usage routing against 17 siblings, the definition is too thin for an agent to invoke correctly.

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% across 4 parameters, so the description carries the full burden and fails to do so. It never mentions start_date, end_date, account, or property_id, and gives no hint about date formats or the meaning of the optional account vs property_id scoping.

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 uses a specific verb ('Read') plus an explicit enumeration of the aggregate metrics returned (users, sessions, engagement, page views, events, key events, revenue). This makes the tool's scope distinguishable from generic report runners like run_report, though it never names that sibling to sharpen the contrast.

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 on when to use this instead of run_report, run_realtime_report, or the specialized tools (get_top_pages, get_events, get_traffic_sources). The word 'aggregate' hints at a summary use case, but no prerequisites, exclusions, or alternatives are stated.

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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