Skip to main content
Glama
swesmith-repos

Meta Ads MCP

search_behaviors

Retrieve behavior targeting options for Meta Ads campaigns to identify audience segments based on user activities and interests.

Instructions

Get all available behavior targeting options.

Args:
    access_token: Meta API access token (optional - will use cached token if not provided)
    limit: Maximum number of results to return (default: 50)

Returns:
    JSON string containing behavior targeting options with id, name, audience_size bounds, path, and description

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
access_tokenNo
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries full burden. It discloses that it returns a JSON string with specific fields (id, name, etc.) and mentions optional token caching, but lacks details on rate limits, error handling, or authentication requirements beyond the optional token. It adequately describes the output format but misses broader behavioral traits.

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 well-structured with clear sections for Args and Returns, using bullet-like formatting without markdown. Every sentence adds value: the purpose, parameter semantics, and return format. It's front-loaded and efficiently conveys necessary information without redundancy.

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 2 parameters, 0% schema coverage, no annotations, and an output schema present, the description is fairly complete. It explains the tool's purpose, parameters, and return values, though it could benefit from more context on usage scenarios or error cases. The output schema reduces the need to detail return values, but some behavioral aspects remain uncovered.

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?

Schema description coverage is 0%, so the description must compensate. It adds meaning by explaining that access_token is optional with caching fallback and limit has a default of 50, which clarifies beyond the schema's basic types and titles. However, it doesn't detail format constraints or usage examples for parameters.

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 clearly states the verb 'Get' and resource 'behavior targeting options', specifying it retrieves 'all available' options. It distinguishes from siblings like search_interests or search_demographics by focusing on behaviors, though it doesn't explicitly compare them.

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 guidance is provided on when to use this tool versus alternatives like search_interests or search_demographics. The description mentions what it returns but not the context or prerequisites for usage, leaving the agent to infer based on tool name alone.

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/swesmith-repos/pipeboard-co__meta-ads-mcp.36128861'

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