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Unilytics MCP Server

Unilytics MCP Server

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demographic_options

Read-only

Retrieve Google Ads demographic targeting options—age ranges, genders, parental status, and household income tiers with API enum values—to build campaign targeting criteria.

Instructions

Get all available Google Ads demographic targeting options.

Returns age ranges, genders, parental status, and household income tiers with their Google Ads API enum values. Useful for building campaign targeting criteria.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "demographic_options"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.1.0
    • removedInput schema / properties / config
      Removed value: -{
      -  "default": null,
      -  "title": "config",
      -  "type": "string"
      -}
  2. First observedv1.0.0

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds value by disclosing what the response contains — the four demographic dimensions and that they carry Google Ads API enum values — which the annotations do not.

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?

Three short sentences, front-loaded with the purpose and followed by return contents and use case. No filler, though the final sentence is mildly redundant with the first.

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 no output schema, the description carries the burden of explaining return values and does so at a useful level of detail (dimensions plus enum values). It stops short of describing the response shape or whether results are static, but nothing essential for calling it is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. The description correctly signals a no-argument, fetch-everything call.

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 and resource ('Get all available Google Ads demographic targeting options') and enumerates the returned categories (age ranges, genders, parental status, income tiers). No sibling tool covers demographic lookups, so no disambiguation is needed.

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?

'Useful for building campaign targeting criteria' implies the usage context but gives no explicit when-to-use/when-not guidance or prerequisites. Adequate but thin for a lookup tool.

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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