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johnoconnor0

Google Ads MCP Server

by johnoconnor0

google_ads_app_conversions

Get app conversion data broken down by install, purchase, action, and engagement categories to understand campaign performance drivers.

Instructions

Get detailed app conversion data by conversion type.

Retrieves app install and in-app engagement conversions broken down by conversion action and category. Useful for understanding which conversion events are driving campaign performance.

Args: customer_id: Google Ads customer ID (10 digits, no hyphens) campaign_id: Optional campaign ID to filter (returns all if not specified) date_range: Date range - LAST_7_DAYS, LAST_30_DAYS, LAST_90_DAYS, etc.

Returns: Dictionary with app conversion data including: - campaigns: Campaign-level conversion breakdown - by_type: Aggregated conversions by category - total_campaigns: Number of campaigns with conversion data

Example: Get conversion breakdown for all app campaigns: google_ads_app_conversions( customer_id="1234567890", date_range="LAST_30_DAYS" )

Conversion Categories: - App Installs: First-time app installations - In-App Purchases: Purchases made within the app - In-App Actions: Custom conversion events (level completed, item viewed, etc.) - App Engagement: Session starts, time in app, etc.

Notes: - Requires Firebase or third-party SDK integration for in-app tracking - Install conversions are automatically tracked - In-app conversions require SDK implementation

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
customer_idYes
campaign_idNo
date_rangeNoLAST_30_DAYS

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the full burden. It clearly describes the output structure (campaign-level breakdown, aggregated by type, total campaigns) and prerequisites (SDK for in-app, automatic install tracking). Implies read-only nature, but does not explicitly state it as safe/read-only.

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?

Well-structured with sections (Args, Returns, Example, Notes, Conversion Categories) and front-loaded purpose. Some minor repetition (e.g., Notes restate SDK requirements from Conversion Categories), but overall efficient.

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?

Given the tool has an output schema (context) and 3 parameters with no enums, the description is very complete. Covers all parameters, output structure, example usage, conversion categories, and prerequisites. No missing critical details.

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 coverage is 0%, but the description compensates fully. Explains each parameter: customer_id format (10 digits, no hyphens), campaign_id as optional filter, date_range with examples of valid values. Also includes an example call, making semantics clear.

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?

Clearly states 'Get detailed app conversion data by conversion type' and elaborates with specific breakdown by conversion action and category. Distinguishes from sibling read tools by focusing on app-specific conversions and listing conversion categories like App Installs, In-App Purchases, etc.

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 clear context on when to use: for understanding which conversion events drive campaign performance. Includes prerequisites in Notes (SDK integration needed for in-app conversions). However, does not explicitly compare or exclude alternatives like get_conversion_performance.

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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