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google-ads-mcp

google-ads-mcp

by eneelkant
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

update_ad_group

Idempotent

Modify existing ad group settings: update name, max CPC bid, target CPA, or status. Only specified fields change.

Instructions

Update an existing ad group.

Only provided fields will be updated.

Args: customer_id: Google Ads customer ID. ad_group_id: Ad group ID to update. name: New ad group name. cpc_bid: New max CPC bid in currency. target_cpa: New target CPA in currency. status: New status -- 'ENABLED', 'PAUSED', or 'REMOVED'.

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": {
      "customer_id": "<customer_id>",
      "ad_group_id": "<ad_group_id>"
    },
    "name": "update_ad_group"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameNo
statusNo
cpc_bidNo
target_cpaNo
ad_group_idYes
customer_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already signal mutation, idempotency, and non-destructiveness, and the description adds the crucial partial-update behavior: unspecified fields are left untouched. It does not discuss response or error semantics, but this is acceptable given annotation coverage and no output schema.

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 summary line, partial-update note, and Args section are compact and well ordered, with no redundant prose. Every sentence contributes to correct invocation.

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?

All six parameters are documented, and partial-update behavior makes invocation requirements clear. It could be more complete by noting what the API returns and by naming sibling tools for status-only or campaign-level updates, but nothing essential for making the call is missing.

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

Parameters5/5

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

Schema descriptions are absent (0% coverage), so the Args block carries the full burden. It defines each parameter's domain, units for monetary bids ('in currency'), and explicit allowed status values, adding real meaning beyond property titles and types.

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 action and resource ('Update an existing ad group') and enumerates the precise mutable fields, making it immediately distinct from create_ad_group, set_ad_group_status, and update_campaign. The 'only provided fields will be updated' line further clarifies the scope.

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?

The use case is implied by the name and summary: modify an existing ad group's optional fields. However, it never explicitly says when to prefer set_ad_group_status for status-only changes or update_campaign for campaign-level edits, leaving routing to the agent's inference.

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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