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google-ads-mcp-server

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google ads get conversion actions

google_ads_get_conversion_actions
Read-onlyIdempotent

List Google Ads conversion actions with status, type, category, primary flags, owner, and last activity dates to audit and manage conversion tracking.

Instructions

List conversion actions with status, type, category, primary/include-in-conversions flags, owner customer, and last activity dates when supported.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of returned items or rows. The declared bounds and default apply; use pagination for additional results.
customerIdYesGoogle Ads customer ID (without dashes, e.g., 1234567890)
statusFilterNoNative status values used to filter the returned entities.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYesOriginal tool result: parsed JSON when the text is JSON, otherwise the text or multiple MCP content blocks. Provider fields depend on the selected query.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv2.0.0
    • addedInput schema / properties / limit / description
      Added value: +"Maximum number of returned items or rows. The declared bounds and default apply; use pagination for additional results."
    • addedInput schema / properties / statusFilter / description
      Added value: +"Native status values used to filter the returned entities."
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "result": {
+      "anyOf": [
+        {
+          "additionalProperties": true,
+          "properties": {},
+          "type": "object"
+        },
+        {
+          "items": {},
+          "type": "array"
+        },
+        {
+          "type": "string"
+        },
+        {
+          "type": "number"
+        },
+        {
+          "type": "boolean"
+        },
+        {
+          "type": "null"
+        }
+      ],
+      "description": "Original tool result: parsed JSON when the text is JSON, otherwise the text or multiple MCP content blocks. Provider fields depend on the selected query."
+    }
+  },
+  "required": [
+    "result"
+  ],
+  "type": "object"
+}
  2. First observedv1.0.0

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the 'when supported' caveat, which usefully signals that some fields may be absent depending on the conversion action type. However, it doesn't disclose pagination behavior, default limits, or how statusFilter interacts with the returned data beyond what the schema already states.

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?

The description is a single sentence that front-loads the primary action ('List conversion actions') and then enumerates the returned fields compactly. It is efficient with no wasted words, though the trailing 'when supported' clause is slightly vague. It earns a 4 rather than 5 because the field enumeration is a bit list-like and could be more scannable.

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 read-only list tool with a rich output schema, full parameter documentation in the schema, and annotations covering safety, the description is largely complete. The main gap is the lack of explicit guidance on when to use this versus run_gaql or get_insights, and the 'when supported' caveat is underspecified. But given the output schema exists and annotations are strong, the description provides sufficient context for correct invocation.

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 three parameters (customerId, limit, statusFilter) with types, defaults, and bounds. The description adds minimal parameter meaning beyond the schema—it mentions status and flags as returned fields, which loosely maps to statusFilter, but doesn't explain how the filter affects results. Baseline 3 is appropriate since the schema carries the parameter documentation burden.

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 clearly states the tool lists conversion actions and enumerates the specific fields returned (status, type, category, flags, owner customer, last activity dates). This distinguishes it from sibling tools like get_campaigns or get_adgroups, though it doesn't explicitly name a sibling alternative. The verb 'List' and resource 'conversion actions' are specific and unambiguous.

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?

The description implies a read-only listing use case but provides no explicit guidance on when to choose this tool over alternatives like run_gaql or get_insights. The 'when supported' caveat hints at data availability limitations, but there is no explicit when-to-use or when-not-to-use guidance. Context is clear enough for an agent to infer basic usage, but exclusions are absent.

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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