Skip to main content
Glama

meta_ads_targeting_search

Search Meta's interest-targeting catalogue by keyword and resolve interest names to internal IDs for ad set targeting specs. Returns audience size bounds, path, and topic per interest.

Instructions

Searches Meta's interest-targeting catalogue by keyword and resolves interest names to the internal IDs used in an ad set's targeting spec (targeting.flexible_spec / interests). Returns id, name, audience_size_lower_bound, audience_size_upper_bound, path, and topic per interest. Read-only. Use this to look up an interest ID before meta_ads_ad_sets_create / update — agents cannot invent these IDs. For behaviors / demographics (which keyword search does not cover) use meta_ads_targeting_categories instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum interests returned. Default 25, max 100.
queryYesInterest keyword to search for (e.g. 'camping', 'yoga'). Must be non-empty.
localeNoOptional Graph locale (e.g. 'ja_JP') to return localized interest names. Omitted when unset.
account_idNoMeta Ads account ID in the format 'act_XXXXXXXXXX' (e.g. 'act_1234567890'). Optional — falls back to META_ADS_ACCOUNT_ID from the configured credentials. The leading 'act_' prefix is required.
Behavior4/5

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

With no annotations provided, the description carries the full burden. It explicitly says 'Read-only' and lists the exact return fields (id, name, audience_size bounds, path, topic). However, it does not disclose error behavior or pagination details, which would add further transparency.

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 concise and information-dense. It front-loads the main purpose, then covers return fields, read-only safety, usage context, and an alternative in a compact paragraph. Every sentence serves a clear function without waste.

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 no output schema, the description compensates by enumerating the return fields. It also situates the tool in the ad-set creation workflow and provides an explicit alternative for other targeting types, making the scope and purpose fully clear.

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?

The schema already provides 100% coverage with clear descriptions for all four parameters. The description adds little beyond reinforcing that the search is by keyword (query). It does not explain limit, locale, or account_id beyond what the schema states, so baseline 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 clearly states the tool's function: it searches Meta's interest-targeting catalogue by keyword and resolves interest names to internal IDs. It also distinguishes it from the sibling tool meta_ads_targeting_categories by noting that behaviors/demographics are not covered.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly instructs to use this tool before meta_ads_ad_sets_create/update, stating that agents cannot invent interest IDs. It also provides a direct alternative for behaviors/demographics: use meta_ads_targeting_categories instead.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/logly/mureo'

If you have feedback or need assistance with the MCP directory API, please join our Discord server