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google-ads-mcp

Official
by googleads

Search Search

search_search
Read-only

Fetches Google Ads data by specifying customer, resource, and fields. Supports conditions, ordering, and row limits for targeted queries.

Instructions

Fetches data from the Google Ads API using the search method

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoThe maximum number of rows to return
fieldsYesThe fields to fetch
resourceYesThe resource to return fields from
orderingsNoHow the data is ordered
conditionsNoList of conditions to filter the data, combined using AND clauses
customer_idYesThe id of the customer

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.3

TDQS

C2.9/5.0
Behavior2/5

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

The readOnlyHint annotation already indicates this is a read operation, and the description adds no behavioral detail beyond that: no mention of pagination, rate limits, result shape, or side effects. 'Fetches data' essentially restates the annotation rather than enriching it.

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 a single concise sentence with no filler and the key verb is front-loaded. It could have packed in more useful detail without becoming bloated, but as written it is appropriately sized for a minimal definition.

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

Completeness2/5

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

Despite a rich schema and an output schema, the description leaves out critical context: why to use this instead of the siblings, what 'search method' means in practice, and any constraints or caveats about the query. For a generic data-fetching tool with six parameters, this is under-specified.

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 the parameters are already well documented. The description does not add any extra meaning about how parameters like fields, resource, or conditions should be used, so the baseline of 3 applies.

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 uses a specific verb ('Fetches') and identifies the resource ('data from the Google Ads API') with a named method ('search method'). It is clear enough to understand the basic operation, but it does not distinguish this tool from the sibling tools customers_list_accessible_customers or metadata_get_resource_metadata, so it earns a 4 rather than a 5.

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 gives no guidance about when to use this tool versus the listed sibling tools, and it does not mention any exclusions or alternative approaches. An agent cannot tell from the description whether to choose this tool or one of its siblings in a given situation.

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