Google Ads MCP Server

get_recommendations

Retrieve optimization recommendations for Google Ads accounts. Identify actionable insights to improve campaign performance and maximize results.

Instructions

Get Google optimization recommendations

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "customerId": "<customerId>"
    },
    "name": "get_recommendations"
  }
}

Input Schema

Name	Required	Description	Default
`types`	No
`customerId`	Yes	Google Ads customer ID

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Aug 9, 2026

TDQS

C2.8/5.0

Behavior2/5

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

No annotations are provided, so the description must convey behavioral traits itself. It simply states 'Get' without disclosing whether this is a read-only operation, how recommendations are filtered, or what the response contains. This is insufficient for the agent to understand the tool's behavior.

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 short sentence, 'Get Google optimization recommendations', with no unnecessary words. It is front-loaded and efficient, though minimal.

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?

Without an output schema or annotations, the description should explain what the tool returns and any relevant context. It does not mention response format, filtering behavior, or how recommendations connect to sibling tools like 'apply_recommendation'. For a two-parameter tool with no output schema, this is incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema describes 'customerId' but leaves 'types' unexplained. The description adds no parameter information, failing to clarify what values 'types' accepts or what 'types' filters. With only 50% schema coverage, the description does not compensate for the missing parameter semantics.

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 the verb 'Get' with the resource 'Google optimization recommendations', clearly indicating this tool retrieves optimization recommendations. However, it does not distinguish itself from sibling tool 'get_budget_recommendations', which is a narrower variant, so the purpose is clear but not differentiated.

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 provides no guidance on when to use this tool versus alternatives like 'get_budget_recommendations' or how it relates to 'apply_recommendation'/'dismiss_recommendation'. There is no context about recommended use cases or exclusions, so the agent is left without decision support.

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

Deploy Server