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AdLoop: Google Ads, Reddit Ads & GA4

by kLOsk
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Ad performance

get_ad_performance
Read-only

Retrieve Google Ads ad-level performance data, including headlines, descriptions, impressions, clicks, CTR, conversions, cost, and policy approval status, to audit and optimize campaigns.

Instructions

Get ad-level performance data including headlines, descriptions, and metrics.

Returns ad type, headlines, descriptions, final URL, impressions, clicks, CTR, conversions, cost for each ad, plus its policy approval status, review status and policy topic names. Disapproved and limited-by-policy ads are listed under policy_issues with their spend.

Google Ads API: https://developers.google.com/google-ads/api/docs/start

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
compactNoWhen true (for audits/overviews), returns totals, the top-10 ads with headline/description COUNTS instead of full asset lists, plus incomplete-RSA, single-ad ad-group and policy findings with approval-status counts (~90% smaller).
customer_idNoGoogle Ads customer ID, digits with or without dashes (e.g. "123-456-7890"). Defaults to the configured ads.customer_id.
date_range_endNoEnd date as "YYYY-MM-DD" (inclusive).
date_range_startNoStart date as "YYYY-MM-DD". Both dates must be set to apply a range; if either is empty, the last 30 days are used.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv0.27.1
    • addedInput schema / properties / compact / description
      Added value: +"When true (for audits/overviews), returns totals, the top-10\nads with headline/description COUNTS instead of full asset lists,\nplus incomplete-RSA, single-ad ad-group and policy findings with\napproval-status counts (~90% smaller)."
    • addedInput schema / properties / customer_id / description
      Added value: +"Google Ads customer ID, digits with or without dashes\n(e.g. \"123-456-7890\"). Defaults to the configured ads.customer_id."
    • addedInput schema / properties / date_range_end / description
      Added value: +"End date as \"YYYY-MM-DD\" (inclusive)."
    • addedInput schema / properties / date_range_start / description
      Added value: +"Start date as \"YYYY-MM-DD\". Both dates must be set\nto apply a range; if either is empty, the last 30 days are used."
  2. Changed1 schema field changedv0.12.0
    • addedInput schema / properties / compact
      Added value: +{
+  "default": false,
+  "type": "boolean"
+}
  3. First observedv0.9.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds useful behavioral context by noting that disapproved and limited-by-policy ads surface under policy_issues with their spend, which tells the agent what to expect from the result.

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?

Purpose is front-loaded in the first sentence, followed by the returned fields and policy handling. The trailing Google Ads API URL is marginally useful documentation but slightly extraneous to the task of invoking the tool.

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?

With annotations covering safety and an output schema present, the description need not explain return values, yet it does so thoroughly and adds the policy_issues behavior. Everything needed to call the tool correctly is present, with mild redundancy against the output schema.

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 description coverage is 100%, so the schema already fully documents all four parameters. The description adds no parameter-level syntax or format detail beyond what the schema provides, making the baseline 3 appropriate.

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?

States a specific verb (Get) and resource (ad-level performance data) and enumerates the fields returned (headlines, impressions, CTR, conversions, etc.). It is clearly distinguishable from get_campaign_performance and get_keyword_performance by scope, though it never names those siblings explicitly for differentiation.

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?

The description gives no when-to-use guidance or exclusions; it never says when to prefer this over get_detailed_asset_performance or get_campaign_performance. The only usage hint (audits/overviews) lives inside the compact parameter schema, not the description.

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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