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google-ads-mcp-server

google_ads_get_shopping_performance

Analyze Google Ads Shopping performance by product dimensions like item ID, brand, and feed label. Filter by campaign or date to connect spend and conversions to merchant products.

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

TableJSON Schema
NameRequiredDescriptionDefault
brandNoOptional product brand filter
limitNo
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
Behavior3/5

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

No annotations are provided, so the description carries more weight. It does disclose the read-only nature and the report's dimensional structure, which is useful, but it leaves out behavioral details like required date/customer scope, pagination, rate limits, or response shape.

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 efficient sentences with no filler. The key read-only qualifier and differentiating dimensions are front-loaded, and the use case follows in the second sentence.

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 the absence of an output schema and annotations, the description provides strong domain context and enough directional detail about what the report contains. The schema covers parameter documentation, so the main remaining gap is a more explicit statement of returned metrics, though 'spend/conversions' partially addresses that.

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 91%, so the schema already documents most parameters. The description adds alignment context by naming product dimensions that map to filters such as merchant ID, item ID, brand, and feed label, but it does not meaningfully supplement the limit or date-format parameters.

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 a read-only Shopping performance report and specifies the distinguishing key: Merchant Center product dimensions. This separates it from sibling tools like google_ads_get_shopping_products and google_ads_get_keyword_performance.

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?

It gives a concrete use case: joining spend/conversions to merchant ID, item ID, title, brand, feed label, and custom labels. This helps an agent know when the report is appropriate, though it does not explicitly state when to prefer alternatives or list exclusions.

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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