Skip to main content
Glama

meta_ads_audiences_list

List Meta Ads custom audiences to find audience IDs for targeting ad sets or creating lookalikes. Includes id, name, subtype, and approximate size.

Instructions

Lists Custom Audiences in a Meta Ads account. Returns id, name, subtype (WEBSITE / CUSTOM / LOOKALIKE / APP / etc.), approximate_count, retention_days, and data_source per audience. Read-only. Use this to find an audience_id before targeting an ad set (meta_ads_ad_sets_create / update) or before creating a lookalike (audiences.create_lookalike). Approximate counts from Meta may lag actual size by 24–48h.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum records returned per call. Default 50, max 1000 per Meta Graph API.
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 transparency burden. It discloses that the operation is read-only and adds a meaningful caveat about approximate counts lagging by 24–48 hours. It does not mention authentication, rate limits, or pagination behavior, but the essentials are covered.

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?

Three sentences, front-loaded with the primary action and return fields. Every sentence adds value, and the usage hint is placed efficiently.

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?

For a simple two-parameter list tool without an output schema, the description is complete: it names the resource, lists return fields, provides the primary use case, and notes the data freshness caveat. No critical context is missing.

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 two parameters are already fully documented in the schema. The description repeats the limit default and account_id fallback but adds no new parameter-level meaning beyond what the schema provides.

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 uses a specific verb and resource: 'Lists Custom Audiences in a Meta Ads account.' It also enumerates the returned fields and clearly distinguishes this list operation from related audience tools like meta_ads_audiences_get, create, or delete.

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?

The description explicitly states when to use the tool: to find an audience_id before targeting an ad set or creating a lookalike. It names the dependent tools but does not explicitly mention when not to use it or name alternative list/get tools, so it stops short of a 5.

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