Meta Ads MCP

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insights_get

Fetch performance metrics for any Meta ad entity (account, campaign, ad set, or ad) with options for date ranges, breakdowns, and filters.

Instructions

Get insights for any entity (account, campaign, ad set, or ad).

Args: entity_id: act_... for an ad account, OR a campaign/adset/ad ID. level: account, campaign, adset, or ad. Determines aggregation. date_preset: today, yesterday, this_week_mon_today, last_7d, last_14d, last_28d, last_30d, last_90d, this_month, last_month, this_quarter, maximum, etc. Mutually exclusive with time_range. time_range: {"since": "YYYY-MM-DD", "until": "YYYY-MM-DD"}. fields: Comma-separated list. Defaults to a comprehensive standard set. breakdowns: e.g. ["age", "gender"], ["publisher_platform", "platform_position"], ["country"], ["device_platform"], ["impression_device"]. action_breakdowns: e.g. ["action_type", "action_destination"]. filtering: e.g. [{"field":"spend","operator":"GREATER_THAN","value":"10"}]. time_increment: 1, 7, monthly, all_days. Aggregates by time buckets. sort: e.g. ["spend_descending"], ["impressions_descending"].

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "entity_id": "<entity_id>"
    },
    "name": "insights_get"
  }
}

Input Schema

Name	Required	Default
`sort`	No
`level`	No	ad
`limit`	No
`fields`	No
`entity_id`	Yes
`filtering`	No
`breakdowns`	No
`time_range`	No
`date_preset`	No
`time_increment`	No
`action_breakdowns`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Aug 1, 2026

TDQS

A3.9/5.0

Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It does provide useful constraints, such as 'date_preset: ... Mutually exclusive with time_range' and 'fields: ... Defaults to a comprehensive standard set.' However, it omits details about response format, pagination, rate limits, authentication, or potential side effects, which are relevant for a data-fetching tool.

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

Conciseness4/5

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

The description opens with a clear one-line purpose and then uses a structured 'Args:' block to document all 11 parameters. Each line is information-dense and uses examples. While it is somewhat long, the format is excellently organized and avoids fluff, earning a high score for structure even if not maximally concise.

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?

The tool has 11 parameters, no output schema, and no annotations, so completeness is challenging. The description covers parameter semantics thoroughly but lacks guidance on when to use this tool versus its siblings and does not describe the return value structure or pagination behavior. Since no output schema exists, the omission of return format is a notable gap.

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

Parameters5/5

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

The schema has 0% description coverage, so the description fully compensates by explaining each parameter with concrete examples. It clarifies entity_id format ('act_... for an ad account, OR a campaign/adset/ad ID'), enumerates date_preset options, gives JSON examples for time_range and filtering, and lists acceptable values for time_increment and sort. This adds substantial meaning beyond the raw schema.

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: 'Get insights for any entity (account, campaign, ad set, or ad).' It uses a specific verb ('Get') and resource ('insights') with an explicit scope covering all entity levels. This differentiates it from sibling tools like insights_get_account_summary (which is account-specific) and the IG/pages insights tools.

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

Usage Guidelines3/5

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

The description implies usage by listing supported entity types and the 'level' parameter ('account, campaign, adset, or ad'), which tells the agent what kinds of entities it can query. However, it does not explicitly say when to choose this tool over sibling tools like insights_get_account_summary or insights_compare_periods, nor does it mention exclusions or alternative conditions.

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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