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scalably-io

google-ads-mcp

by scalably-io

google_ads_list_customer_clients

Read-only

Walk the Google Ads MCC hierarchy to list all customer client accounts under a manager account. Returns each client's ID, name, currency, time zone, and status, including hidden and manager accounts.

Instructions

Walk the MCC (Manager Account) hierarchy and return every child account.

For agency use: this is the canonical "which clients can I query?" call. Uses GAQL on the customer_client resource. Fast: one streaming call.

Args: mcc_customer_id: MCC customer_id. Defaults to GOOGLE_ADS_LOGIN_CUSTOMER_ID (the configured MCC). Accepts 10-digit or hyphenated. include_managers: include sub-MCCs in the result (default True). include_hidden: include customer_clients marked hidden=True (default False). max_level: max hierarchy depth (default 3, hard cap 10).

Returns per account: customer_id, descriptive_name, currency_code, time_zone, manager (bool), level, status (ENABLED|CANCELED|…), hidden, resource_name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
max_levelNo
include_hiddenNo
mcc_customer_idNo
include_managersNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses meaningful behavior: it walks hierarchy, includes sub-MCCs by default, excludes hidden accounts by default, enforces a default max depth of 3 with a hard cap of 10, and uses a single streaming call. These details materially help an agent predict side effects and performance.

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 well structured with a clear opening statement, a usage context sentence, and organized Args/Returns sections. Every sentence adds value; there is no filler or repetition.

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

Completeness5/5

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

The description covers purpose, parameters, return fields, defaults, and constraints such as the hard depth cap. Even with an output schema present, it provides enough context for an agent to invoke the tool correctly without guessing.

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 description coverage is 0%, so the description carries full responsibility for parameter semantics. It explains all four parameters clearly, including defaults, accepted formats for mcc_customer_id, and the meaning of include_managers, include_hidden, and max_level.

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 clearly states the tool's purpose: walk the MCC hierarchy and return every child account. It names the underlying resource and GAQL approach, and frames it as the canonical 'which clients can I query?' call, distinguishing it from general query tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives a clear use case ('For agency use: this is the canonical which clients can I query? call') and notes it is fast and streaming. It does not explicitly name alternatives or state when not to use it, but the intended context is obvious.

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