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AdsAgent — Google Ads MCP

google_ads_accounts_list

Read-only

List accessible Google Ads accounts (synced data by default). Manager accounts are listed but cannot be queried for metrics; only enabled non-manager accounts can.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceNoRead source; defaults to synced data ('ledger'). 'live' sweeps the API.
connection_contextNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / source / description
      Previous value: -"Read source; defaults to the Supabase ledger. 'live' sweeps the API."New value: +"Read source; defaults to synced data ('ledger'). 'live' sweeps the API."
  2. Changed1 schema field changed
    • addedInput schema / properties / connection_context
      Added value: +{
      +  "pattern": "^mctx_v1_[0-9a-f]{64}$",
      +  "type": "string"
      +}
  3. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds genuine behavioral context beyond that: manager accounts appear in the result but are unusable for metrics, and results come from synced data unless overridden. Return format and pagination remain undisclosed, keeping it out of 5 territory.

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?

Two sentences with no filler; the verb+resource leads and the caveat follows. Slightly dense in the second sentence, but every clause carries information an agent needs.

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

Completeness3/5

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

With no output schema and only partial parameter documentation, the description should say more about what the returned accounts look like and how connection_context must be supplied. The metric-eligibility caveat is valuable but leaves the auth parameter and result shape unaddressed.

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 coverage is 50%: the 'source' enum is fully documented in the schema, and the description reinforces its default ('synced data by default'). connection_context has no description anywhere, and the description does not compensate. Baseline 3 is appropriate since the schema carries most of the parameter meaning.

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 gives a specific verb and resource ('List accessible Google Ads accounts') and scopes it to synced data by default. It does not name or contrast with the closely related siblings google_ads_accounts_pull, google_ads_accounts_sync, or google_ads_connections_list, so the agent must infer which of these to pick.

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?

It states a meaningful precondition for downstream use ('only enabled non-manager accounts can' be queried for metrics), which implies the tool's role. But it never says when to call this versus the pull/sync/connections siblings, and there is no explicit exclusion guidance, leaving selection to 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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