Google Ads MCP Server

apply_labels

Apply labels to Google Ads campaigns, ad groups, or ads. Specify customer ID, resource type and IDs, and label IDs to organize and filter your resources.

Instructions

Apply labels to campaigns/ads

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>",
      "resourceType": "<resourceType>",
      "resourceIds": "<resourceIds>",
      "labelIds": "<labelIds>"
    },
    "name": "apply_labels"
  }
}

Input Schema

Name	Required	Description
`labelIds`	Yes
`customerId`	Yes	Google Ads customer ID
`resourceIds`	Yes
`resourceType`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Aug 9, 2026

TDQS

C2.7/5.0

Behavior2/5

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

Annotations are absent, so the description carries full burden. It only says 'apply labels' without disclosing whether labels are added, replaced, or removed, whether the operation is idempotent, or any side effects. As a mutation tool, this lack of behavioral detail is a significant gap.

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, direct sentence with no wasted words, making it concise and front-loaded. However, it is arguably too terse, bordering on under-specification, though that is more a completeness issue than a conciseness one.

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?

This is a mutation tool with 4 required parameters, no annotations, and no output schema. The description provides only the basic action and resource, without addressing the ad_group option, prerequisites, or operational behavior. It is insufficient for an agent to correctly invoke the tool in varied contexts.

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?

Schema description coverage is only 25% (only customerId has a description). The description does not clarify that resourceType must be one of campaign, ad_group, or ad, nor that resourceIds must match that type. It doesn't explain the relationship between labelIds, resourceIds, and resourceType beyond the tool name, providing minimal compensation for the low schema coverage.

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 states a specific action ('Apply labels') and the target resource ('campaigns/ads'), which clearly differentiates it from sibling tools like create_labels (creating labels) and get_labeled_resources (retrieving labels). However, it omits 'ad_group' even though resourceType enum includes it, making the stated scope slightly incomplete.

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?

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., labels must already exist via create_labels), exclusions, or typical use cases. The minimal description leaves usage entirely to inference.

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

Deploy Server