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google ads get insights

google_ads_get_insights

Read-onlyIdempotent

Get Google Ads performance insights by auto-generating GAQL queries, automatically splitting incompatible metrics and segments to deliver accurate data.

Instructions

Query Google Ads performance insights with intelligent query planning. Auto-generates GAQL, handles metric/segment incompatibilities by splitting queries. Use google-ads://metrics for available metrics, google-ads://dimensions for dimensions.

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
`metrics`	Yes	Metric keys (e.g., impressions, clicks, cost_micros, conversions)
`orderBy`	No	Optional GAQL field to order by, e.g. metrics.impressions or campaign.name
`resource`	No	GAQL FROM clause resource type (campaign, ad_group, ad_group_ad, keyword_view, shopping_performance_view, asset_group, geographic_view, video, search_term_view, landing_page_view, etc.)	campaign
`startDate`	No	Start date YYYY-MM-DD
`customerId`	Yes	Google Ads customer ID (without dashes, e.g., 1234567890)
`datePreset`	No	Predefined date range
`dimensions`	No	Dimension keys (e.g., date, campaignName, device)
`orderDirection`	No	Sort direction for the selected ordering field.	DESC

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

A3.9/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the description does not need to restate safety. It adds valuable behavior beyond annotations: it 'auto-generates GAQL' and 'handles metric/segment incompatibilities by splitting queries.' This is the kind of non-obvious runtime behavior an agent needs to know when invoking the tool.

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?

The description is two sentences with no filler. The core capability is front-loaded, the key automatic behavior follows immediately, and the last sentence directs the agent to additional resources. Every sentence earns its place.

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 10-parameter tool with a rich schema and an output schema, the description covers the main non-obvious aspects: automatic GAQL generation, query splitting, and where to look up valid metric/dimension keys. It is slightly incomplete on when to choose this tool over google_ads_run_gaql or the specific get_* tools, but the schema and annotations compensate well.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3 because the schema already documents all parameters. The description adds value beyond the schema by telling the agent to use google-ads://metrics and google-ads://dimensions to discover valid values for the metrics and dimensions parameters. That is helpful for correctly populating those array parameters.

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 clear action and resource: 'Query Google Ads performance insights with intelligent query planning.' It also conveys a distinctive behavior—auto-generating GAQL and splitting incompatible metric/segment queries—which helps separate it from raw GAQL tools like google_ads_run_gaql. However, it does not explicitly name or contrast sibling tools, so some ambiguity remains against the many get_* siblings.

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

Usage Guidelines3/5

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

The description implies when to use the tool: when someone wants Google Ads insights without manually constructing GAQL, and when metric/segment incompatibilities need automatic handling. It also points to google-ads://metrics and google-ads://dimensions for valid values. But it gives no explicit when-not-to-use guidance or alternatives, and with closely related siblings like google_ads_run_gaql this is a meaningful gap.

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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