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scalably-io

Google Analytics 4 MCP

by scalably-io

ga4_list_google_ads_links

Read-only

Identify Google Ads accounts linked to a GA4 property to confirm Ads-to-GA4 cross-reporting availability before querying Ads dimensions.

Instructions

List Google Ads links attached to a GA4 property.

Returns customer_id (the Ads account), can_manage_clients, ads_personalization_enabled, and creator_email. Useful to confirm Ads ↔ GA4 cross-reporting availability before querying Ads-related dimensions like sessionGoogleAdsCampaignId.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
property_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds useful scoping and return-field context, but does not disclose pagination, error behavior, or prerequisites. No contradiction with annotations.

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?

Three tight sentences with no filler. The action is front-loaded, return fields are briefly listed, and the practical use case earns its place. Well-structured for an agent to parse quickly.

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?

For a one-parameter read-only list tool with an output schema, the description covers purpose, returned fields, and the key decision context. The only notable gap is the property_id format, which keeps it from being fully complete.

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 0%, so the description bears the burden for explaining property_id. It only implies the parameter is the GA4 property via 'attached to a GA4 property'; it does not clarify the expected format (e.g., numeric ID vs. 'properties/123456789') or any constraints. This is insufficient compensation for the missing schema description.

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?

States a specific verb ('List'), a concrete resource ('Google Ads links attached to a GA4 property'), and names returned fields. This clearly distinguishes it from sibling list tools such as ga4_list_custom_dimensions or ga4_list_key_events even without opening the schema.

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?

Provides a concrete use case: confirm Ads↔GA4 cross-reporting availability before querying Ads-related dimensions. It does not explicitly name alternatives or when-not-to-use conditions, but the intended context is clear enough to guide selection.

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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