Skip to main content
Glama
estapel-ai

mcp-facebook-ads

by estapel-ai

search_interests

Find Facebook interest targeting options by query to build precise ad audiences. Returns matching interests with limits for audience research.

Instructions

Search interest targeting options.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.4/5.0
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, and it delivers almost nothing. It does not state whether results are paginated, ranked, capped by limit, or whether any auth/permission is required. Only the implicit read-only nature of 'Search' is conveyed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single short sentence is efficient and front-loaded, but at this length it is under-specified rather than truly concise. It earns its place but leaves obvious room to add parameter and usage detail without bloat.

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

Completeness2/5

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

With an output schema present, return values need not be explained, and that lowers the bar. Still, for a 2-param search tool with zero schema coverage and no annotations, the description omits query semantics, limit behavior, and sibling differentiation, leaving the agent under-equipped to call it correctly.

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

Parameters2/5

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

Schema description coverage is 0%, so the schema documents neither parameter beyond its title. The description says nothing about the query string's semantics (free text? exact match?) or the limit parameter (default 25, but max/behavior unknown). It fails to compensate for the coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (Search) and resource (interest targeting options), so the basic purpose is clear. However, it does not differentiate from close siblings like search_behaviors and search_demographics, which an agent could easily confuse it with. Vague enough that scope (what an 'interest' is, granularity) is left to inference.

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

Usage Guidelines2/5

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

No when-to-use guidance and no mention of alternatives. Given three near-identical search_* siblings (interests, behaviors, demographics), the absence of routing guidance is a real gap. The agent must guess from the name alone.

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