Google Analytics 4 by Get MCP Ads

ga4 get key events

ga4_get_key_events

Read-onlyIdempotent

Retrieve key events and conversion counts from Google Analytics 4 property using Data API reports. Returns event names and counts for analysis.

Instructions

Inventory GA4 key events/conversions using metadata-aware Data API reports. Returns best-effort event names and counts.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	Maximum number of returned items or rows. The declared bounds and default apply; use pagination for additional results.
`endDate`	No	End date YYYY-MM-DD or relative (today, yesterday)
`startDate`	No	Start date YYYY-MM-DD or relative (7daysAgo, yesterday)
`datePreset`	No	Named reporting period. Use the custom date range when you need exact start and end dates.	last28days
`propertyId`	Yes	GA4 property ID (numeric, e.g., 123456789)

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes	Original tool result: parsed JSON when the text is JSON, otherwise the text or multiple MCP content blocks. Provider fields depend on the selected query.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.0.1Sep 23, 2026

TDQS

A3.8/5.0

Behavior3/5

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

Annotations already cover the read-only, idempotent, and non-destructive profile. The description adds 'metadata-aware Data API reports' and 'best-effort' as behavioral context, which hints at approximate results and a metadata-based approach, but it doesn't explain exactly why results are best-effort or what 'metadata-aware' means operationally.

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 short sentences front-load the action and resource, then add the key return-value detail. There is no filler or redundant restatement of the tool name, and the description earns its length.

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

Completeness4/5

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

For a read-only inventory tool with thorough parameter documentation, an output schema, and safety annotations, the description covers the core purpose and return type. The only notable gap is the vague 'metadata-aware' phrasing, but it doesn't block correct invocation.

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?

Schema description coverage is 100%, so all five parameters are already documented with defaults, bounds, formats, and enum choices. The description adds no new parameter-level detail beyond the schema, so the baseline score of 3 is appropriate.

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 states a specific action ('Inventory') on a specific resource ('GA4 key events/conversions') and notes the return content ('best-effort event names and counts'). It is clear and distinguishable from siblings like ga4_get_event_parameters or ga4_run_report, though it doesn't explicitly name those alternatives.

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?

The description clearly implies when to use it: when you need an inventory of GA4 key events/conversions with counts. It does not provide explicit 'do not use when' guidance or name alternatives, but the intended context is unmissable and the 'best-effort' qualifier signals a limitation.

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