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Execute Google Ads report

google_ads_execute_report
Read-only

Execute a structured Google Ads GAQL query for one account and return the result rows as TSV (tab-separated, header row + one row per line). Report and field names are those of the Google Ads API GAQL reporting schema. Monetary '*_micros' fields are returned in the account's currency (value divided by 1,000,000) with the '_micros' suffix dropped from the column name (e.g. 'metrics.cost_micros' is returned as 'metrics.cost'). This renaming affects only the returned columns; the GAQL must still select and order by the real field names (e.g. 'metrics.cost_micros'). On a Google API error a detailed message describing the problem is returned.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoOptional maximum number of rows (GAQL LIMIT).
fieldsYesGAQL fields to select, e.g. ["campaign.name", "metrics.clicks", "metrics.impressions"].
reportYesGoogle Ads report/resource to query, e.g. "campaign", "ad_group", "keyword_view", "ad_group_ad".
endDateNoOptional end date (yyyy-MM-dd); startDate is required when set.
orderByNoOptional ORDER BY entries, e.g. ["metrics.clicks DESC"].
accountIdYesTrueClicks account id (the numeric Id field from the account listing, not the Google Ads customer id / ClientCustomerId). Must be a Google Ads account accessible by the connector.
startDateNoOptional start date (yyyy-MM-dd); endDate is required when set.
predicatesNoOptional GAQL WHERE predicates, e.g. ["campaign.status = 'ENABLED'", "metrics.impressions > 0"].

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedInput schema / properties / accountId / description
      Previous value: -"Ad platform account ID to query (must be a Google Ads account accessible by the connector)."New value: +"TrueClicks account id (the numeric Id field from the account listing, not the Google Ads customer id / ClientCustomerId). Must be a Google Ads account accessible by the connector."
  2. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations indicate read-only, open-world, and non-destructive behavior, and the description does not contradict them. It adds useful behavioral detail about output formatting and error handling, though it does not mention limits or pagination.

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 efficient and well structured, with examples that clarify usage. The micros renaming point is explained twice but the repetition serves to prevent a common mistake, so it remains justified.

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?

Given no output schema, the description sufficiently explains the return format (TSV with header and rows) and error behavior. It does not cover edge cases like empty results or pagination, but it is complete enough for typical query execution.

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?

Schema coverage is complete, and the description adds significant meaning: it distinguishes accountId from Google Ads customer id, explains date dependencies, and gives concrete examples for fields, predicates, and ordering. This goes well beyond the raw schema.

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?

The description clearly identifies the tool as executing a structured Google Ads GAQL query for one account and returning results as TSV. It specifies the resource and query nature, distinguishing it from listing/column-discovery sibling tools.

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?

The description explains what the tool does but does not state when to use it versus alternatives like google_ads_report_columns or google_ads_reports_list. There is no explicit when-to-use or when-not-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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TDQS

A3.9/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but the audit and report tools (e.g., audit_rule_output_table vs audit_rule_output_table_historical vs audit_rule_result vs audit_rule_result_campaign) are closely related and rely on detailed descriptions to differentiate.

Naming Consistency4/5

Naming is generally consistent with snake_case and domain-prefixed groups (google_ads_*, ms_ads_*, perfmon_*), though a few tools are bare nouns (account, task, user) rather than verb-led, which slightly deviates from the dominant pattern.

Tool Count4/5

23 tools is on the higher end but justified for a platform covering multiple ad platforms, audit reports, alerts, and user management; it remains navigable with clear groupings.

Completeness4/5

The tool set comprehensively covers account enumeration, audit results, report execution for major ad platforms, perfmon alerts, pacing targets, tasks, and users. Minor gaps exist (e.g., no create/update/modify operations), but the core analytics and monitoring surface is well covered.

Resources