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mikusnuz

meta-ads-mcp

by mikusnuz
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TypeScript
Remote

search_targeting

Find valid Meta ad targeting IDs by keyword for interests, behaviors, and demographics, so you can use them in ad set targeting specs.

Instructions

Search for targeting options (interests, behaviors, demographics, etc.) by keyword. Use this to find valid targeting IDs for ad set targeting specs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesSearch query (e.g. 'fitness', 'technology', 'cooking')
typeNoTargeting type filter: adinterest, adgeolocation, adeducationschool, adeducationmajor, adworkemployer, adworkposition, adlocale, etc.
limitNoNumber of results (default 25)
account_idNoAd account ID to query (e.g. 'act_123' or '123'). Falls back to META_AD_ACCOUNT_ID env var if omitted.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.6.1
    • addedInput schema / properties / account_id
      Added value: +{
+  "description": "Ad account ID to query (e.g. 'act_123' or '123'). Falls back to META_AD_ACCOUNT_ID env var if omitted.",
+  "type": "string"
+}
  2. First observedv1.2.0

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It implies a read-only search, but does not disclose authentication needs, rate limits, pagination behavior, or what the response looks like. For an unannotated search tool, this leaves significant behavioral gaps.

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?

Two sentences, front-loaded with the tool's purpose, then the intended use. There is no wasted text and the most important information comes first.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

It covers the core purpose and usage, and the schema supplies all parameter details. But with no annotations and no output schema, the description should do more to explain the result structure or search behavior. It is minimally adequate but leaves the agent inferring return format and operational constraints.

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 input schema already documents q, type, limit, and account_id in detail. The description adds only the keyword-search context and does not supplement the parameters beyond what the schema provides. Baseline 3 is appropriate.

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 uses the specific verb 'Search' with the resource 'targeting options' and gives examples (interests, behaviors, demographics). It clearly states the outcome, finding valid targeting IDs for ad set targeting specs, though it does not explicitly differentiate from siblings like search_targeting_map or get_targeting_suggestions.

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?

It gives clear usage context: 'Use this to find valid targeting IDs for ad set targeting specs.' That tells the agent when this tool is appropriate. However, it does not name alternatives or exclusions, such as when to use search_targeting_map or get_targeting_suggestions instead.

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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