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google-ads-mcp-server

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google ads suggest geo targets

google_ads_suggest_geo_targets
Read-onlyIdempotent

Resolve up to 25 location names or geo target IDs into Google Ads geoTargetConstants. Returns criterion IDs, canonical names, target types, status, parents, locale, and approximate reach; read-only.

Instructions

Resolve up to 25 location names or geo target IDs to Google Ads geoTargetConstants. Returns criterion IDs, canonical names, target types, status, parents, locale, and approximate reach. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
localeNoLocale used for human-readable lookup results.en
countryCodeNoCountry code used to localize keyword or targeting results.
geoTargetIdsNoGoogle Ads geo-target constant IDs for the intended locations.
locationNamesNoHuman-readable location names for Google to resolve into geo-target constants.

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. Changed5 schema fields changedv2.0.0
    • addedInput schema / properties / countryCode / description
      Added value: +"Country code used to localize keyword or targeting results."
    • addedInput schema / properties / geoTargetIds / description
      Added value: +"Google Ads geo-target constant IDs for the intended locations."
    • addedInput schema / properties / locale / description
      Added value: +"Locale used for human-readable lookup results."
    • addedInput schema / properties / locationNames / description
      Added value: +"Human-readable location names for Google to resolve into geo-target constants."
    • 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

A3.8/5.0
Behavior3/5

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

The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is fully covered without the description. The description adds 'approximate reach' and a limit of 25 inputs, which is useful, but those details are also present in the schema and output schema; it does not disclose rate limits, quota behavior, or any edge-case behavior beyond that.

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?

The description is two sentences with zero filler: the first sentence captures the core action, inputs, and output, and the second sentence notes the read-only nature. The key scoping information ('up to 25') is front-loaded, making the description fast to parse.

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?

Given that the schema fully documents all parameters, the output schema exists, and annotations cover read-only/idempotent/non-destructive behavior, the description provides enough context to call the tool correctly. A minor ambiguity is whether locationNames and geoTargetIds can be used together or are mutually exclusive, which is not explicitly clarified.

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%, and each parameter already has a meaningful description in the schema. The tool description adds only a collective restatement ('location names or geo target IDs') without enriching individual parameter semantics, so the baseline score of 3 is appropriate.

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?

The description states a specific verb ('Resolve'), a clear resource ('Google Ads geoTargetConstants'), and the input forms ('location names or geo target IDs'), which makes the tool's function immediately identifiable. It also lists the output fields, setting it apart from all sibling tools, none of which share this geo-target resolution purpose.

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 when to use the tool—whenever someone needs to resolve location names or IDs to Google Ads geo-target constants—but it does not explicitly state when to use it versus alternatives or when not to use it. Since no sibling tool overlaps in purpose, the absence of an explicit alternative exclusion is less critical, but the guidance is still inferred rather than stated.

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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