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AdLoop: Google Ads, Reddit Ads & GA4

by kLOsk
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Campaign performance

get_campaign_performance
Read-only

Fetch campaign-level metrics like impressions, clicks, cost, conversions, CPA, ROAS and CTR for a date range to analyze performance and spot budget-limited converters.

Instructions

Get campaign-level performance metrics for a date range.

Returns campaign name, status, type, impressions, clicks, cost, conversions, CPA, ROAS, CTR for each campaign, plus Search impression share and the share lost to budget and to ad rank (fractions with matching *_pct percentages; null for campaigns that do not serve on Search or had no impressions). Insights flag converting campaigns that lose a significant share of impressions to budget.

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
compactNoWhen true (for audits/overviews on large accounts), returns account totals, status/type breakdowns, the top-10 spenders, zero-conversion offenders and budget-limited converters instead of every row (~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 on large accounts), returns\naccount totals, status/type breakdowns, the top-10 spenders,\nzero-conversion offenders and budget-limited converters instead\nof every row (~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. Addedv0.13.2
  3. Removedv0.13.0
  4. Changed1 schema field changedv0.12.0
    • addedInput schema / properties / compact
      Added value: +{
+  "default": false,
+  "type": "boolean"
+}
  5. First observedv0.9.0

TDQS

A3.9/5.0
Behavior4/5

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 still adds real behavioral context: which fields are returned, that impression-share values are paired fractions with matching *_pct percentages, that they are null for non-Search or zero-impression campaigns, and that an insights flag calls out budget-limited converters.

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 return details and a reference link. The prose is dense but largely earns its place; the trailing API documentation URL is boilerplate but short.

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?

An output schema exists, so return values need not be explained, yet the description still enumerates them usefully along with the null and insights semantics. Combined with complete annotation and schema coverage, an agent has enough to invoke it correctly; only explicit sibling routing is absent.

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 documents all four parameters including date defaults, the customer_id format, and the compact flag. The description adds no parameter syntax or constraints beyond what the schema provides, so the baseline of 3 applies.

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 (get), resource (campaign-level performance metrics), and scope (for a date range). The campaign-level framing distinguishes it from siblings like get_ad_performance, get_keyword_performance, and get_pmax_performance without needing to open any schema.

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?

Usage is only implied by the tool name and the date-range scope; there is no explicit 'use this when' guidance and no routing to or away from the many sibling performance tools (get_ad_performance, get_pmax_performance, get_audience_performance). The compact parameter's purpose is explained in the schema rather than 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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