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get-mcp-ads

Google Ads by Get MCP Ads

google ads get recommendations

google_ads_get_recommendations
Read-onlyIdempotent

Retrieve Google Ads recommendations with type, resource links, and impact. Filter by recommendation type and include dismissed items to identify optimization opportunities.

Instructions

List Google Ads recommendations with type, resource, campaign/ad group links, dismissed state, and impact when supported.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of returned items or rows. The declared bounds and default apply; use pagination for additional results.
customerIdYesGoogle Ads customer ID (without dashes, e.g., 1234567890)
typeFilterNoOptional RecommendationType enum filter
includeDismissedNoInclude recommendations already dismissed in the account.

Output Schema

TableJSON 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. First observedv2.0.1

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnly, openWorld, idempotent, and not destructive, so the safety burden is covered. The description adds the useful caveat that impact is reported only 'when supported' and enumerates returned dimensions, but it does not disclose default filtering of dismissed recommendations or pagination behavior. It does not contradict the annotations.

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 a single front-loaded sentence that states the action and result payload without filler or repetition of schema details. Every word 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?

Given a rich output schema, complete parameter descriptions, and strong read-only annotations, the description covers the essential behavior well. The only missing contextual aspects are the default includeDismissed behavior and explicit mention of alternatives, but these do not create a serious gap.

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 schema already documents all four parameters with defaults, bounds, patterns, and examples. The description adds no parameter-level semantics beyond hinting at output fields, which is acceptable at the baseline for fully covered schemas.

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 opens with a specific verb ('List') and a clear resource ('Google Ads recommendations'), then names the exact fields returned: type, resource, campaign/ad group links, dismissed state, and impact. This is enough to distinguish it from the many sibling google_ads_get_* tools because no sibling targets recommendations as a resource.

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?

There is no explicit 'use this instead of X' guidance or exclusionary note, so the tool does not differentiate itself from alternatives like run_gaql or get_insights. The intended use case is implied by the resource name and listing behavior, but the description never states when to prefer this tool or what it will not do.

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