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iammalego

mlg-meta-mcp

by iammalego

getInsights

Retrieve performance metrics for accounts, campaigns, ad sets, or ads. Use date presets or custom ranges to access spend, results, and CPR for clear campaign insight.

Instructions

Get performance metrics for accounts, campaigns, adsets, or ads. Supports date presets (yesterday, last_7d, etc) or custom date ranges. Account level returns an aggregated summary; campaign/adset/ad levels also return structured per-item metrics with normalized ids/names plus spend, results, and CPR so consumers can filter and interpret the full signal.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
levelYesAggregation level for metrics
objectIdYesID of account (act_XXX), campaign, adset, or ad
timeRangeNoCustom date range (alternative to datePreset)
datePresetNoPredefined date range. Ignored if timeRange is specified.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A3.8/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden — and it delivers: it discloses the return-shape difference between account level (aggregated summary) and campaign/adset/ad levels (per-item metrics with normalized ids/names, spend, results, CPR). It does not cover pagination or error behavior, but the structural disclosure is strong for a metrics 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?

Two focused sentences with no filler. The core capability and supported levels are front-loaded, and the return-shape clarification is appended where it belongs. Could be tightened slightly but is appropriately sized.

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?

With no output schema, the description must explain return values — it does, clarifying the aggregated vs per-item distinction and listing the metric fields. For a read-only metrics tool with well-documented parameters, the remaining gaps (pagination, max range limits) are minor.

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 coverage is 100% with detailed parameter descriptions (enum values, format hints, precedence between timeRange and datePreset). The description adds real value beyond the schema by explaining what each level actually returns, which is the most ambiguous part of the contract.

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 uses a clear verb+resource ('Get performance metrics for accounts, campaigns, adsets, or ads') and distinguishes levels of aggregation. It does not explicitly name sibling tools to differentiate from, but the purpose is specific enough to separate it from discovery tools like getCampaigns/getAdSets.

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?

Usage context is implied rather than stated: the description tells what it returns but never says when to choose this over getCampaignDetails, getAdSetDetails, or compareTwoPeriods. With 30 siblings, explicit routing guidance would materially help an agent pick correctly.

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