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google ads get shopping performance

google_ads_get_shopping_performance
Read-onlyIdempotent

Retrieve read-only Google Ads Shopping performance data by Merchant Center product dimensions, including spend, conversions, item ID, title, brand, and feed labels for product-level reporting and analysis.

Instructions

Read-only Shopping performance report keyed by Merchant Center product dimensions. Useful for joining spend/conversions to merchant ID, item ID, title, brand, feed label, and custom labels.

Input Schema

NameRequiredDescriptionDefault
brandNoOptional product brand filter
limitNoMaximum number of returned items or rows. The declared bounds and default apply; use pagination for additional results.
itemIdNoOptional Merchant Center item ID filter
endDateYesEnd date YYYY-MM-DD
adGroupIdNoOptional ad group ID filter
feedLabelNoOptional product feed label filter
startDateYesStart date YYYY-MM-DD
campaignIdNoOptional campaign ID filter
customerIdYesGoogle Ads customer ID (without dashes, e.g., 1234567890)
titleContainsNoOptional product title substring filter
merchantCenterIdNoOptional Merchant Center ID filter

Output Schema

NameRequiredDescriptionDefault
resultYesOriginal 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.

  1. Changed8 schema fields changedv2.1.1
    • removedInput schema / additionalProperties
      Removed value: -false
    • removedInput schema / properties / adGroupId / $ref
      Removed value: -"#/properties/campaignId"
    • addedInput schema / properties / adGroupId / pattern
      Added value: +"^\\d+$"
    • addedInput schema / properties / adGroupId / type
      Added value: +"string"
    • removedInput schema / properties / merchantCenterId / $ref
      Removed value: -"#/properties/campaignId"
    • addedInput schema / properties / merchantCenterId / pattern
      Added value: +"^\\d+$"
    • addedInput schema / properties / merchantCenterId / type
      Added value: +"string"
    • changedOutput schema / properties / result / anyOf
      Previous value: -[
      -  {
      -    "additionalProperties": true,
      -    "properties": {},
      -    "type": "object"
      -  },
      -  {
      -    "items": {},
      -    "type": "array"
      -  },
      -  {
      -    "type": "string"
      -  },
      -  {
      -    "type": "number"
      -  },
      -  {
      -    "type": "boolean"
      -  },
      -  {
      -    "type": "null"
      -  }
      -]New value: +[
      +  {
      +    "additionalProperties": {},
      +    "properties": {},
      +    "type": "object"
      +  },
      +  {
      +    "items": {},
      +    "type": "array"
      +  },
      +  {
      +    "type": "string"
      +  },
      +  {
      +    "type": "number"
      +  },
      +  {
      +    "type": "boolean"
      +  },
      +  {
      +    "type": "null"
      +  }
      +]
  2. First observedv2.0.1

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=true, so 'Read-only' in the description is a restatement. The description does add genuine context by naming the report's keying dimensions (Merchant Center product attributes), which tells the agent what grain the rows are returned at. No mention of pagination or limits, though the schema's limit param covers that.

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?

Two tight sentences, front-loaded with the core purpose (read-only Shopping performance report) before the use case. Only 'Read-only' is redundant with annotations; otherwise there is no filler.

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?

With 11 params at full schema coverage, an output schema, and rich annotations, the description only needs to establish purpose and row grain, which it does. Minor omission: no hint about date-range scope or pagination behavior, but both are documented in the schema.

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 every parameter is already self-documenting; baseline 3 applies. The description's field list (merchant ID, item ID, title, brand, feed label) loosely mirrors existing filter params, and 'custom labels' has no corresponding parameter, so it adds little beyond the schema.

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?

States a specific verb and resource: a read-only Shopping performance report keyed by Merchant Center product dimensions, and lists the metrics (spend/conversions) it surfaces. This implicitly separates it from google_ads_get_shopping_products (product catalog listing) and google_ads_get_campaigns, though it never names a sibling explicitly.

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 phrase 'Useful for joining spend/conversions to merchant ID, item ID, title, brand, feed label' implies a use case but gives no explicit when-to-use/when-not guidance or routing to alternatives like google_ads_run_gaql or google_ads_get_shopping_products. Usage must be inferred.

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