Skip to main content
Glama
Pauesome

Ads Analytics MCP

by Pauesome

get_meta_campaign_performance

Retrieve Meta ad campaign metrics: spend, ROAS, CTR, CPA, filtered by date, account, campaign, or status to analyze ad results.

Instructions

Retrieves Meta (Facebook/Instagram) campaign performance metrics for a client. Returns normalized metrics: spend, impressions, clicks, reach, CTR, CPC, CPM, conversions, CPA, conversion value, ROAS. Supports filtering by date range, ad account IDs, campaign IDs, and campaign status. Data is returned at campaign × day granularity. Use list_clients to see available client IDs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusesNoFilter by campaign status. Returns all statuses if omitted.
client_idNoClient identifier. Required when multiple clients are configured. Use list_clients to see available IDs.
campaign_idsNoFilter to specific campaign IDs. Returns all campaigns if omitted.
ad_account_idsNoOverride the client's default Meta ad account IDs (format: act_XXXXXXXXX or plain ID).
date_range_endNoEnd date in YYYY-MM-DD format. Defaults to today.
date_range_startNoStart date in YYYY-MM-DD format. Defaults to 30 days ago.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description bears the full burden. It discloses the return granularity (campaign × day) and enumerates returned metrics, which is helpful. But it doesn't mention authentication needs, rate limits, pagination behavior, or what happens when client_id is omitted but multiple clients are configured (schema hints it's required then, but description is silent).

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?

Four sentences, each front-loaded and informative: purpose, return metrics, filtering, granularity, and a pointer to list_clients. No redundancy or filler.

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 description covers purpose, filters, and return granularity, but with no annotations and no output schema, it should do more to disclose behavioral traits like required permissions or default behaviors when parameters are omitted. It's adequate but not rich enough for a tool with six optional parameters.

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 schema already documents all six parameters in detail. The description adds only a high-level overview of filters (date range, account/campaign IDs, status) without adding syntax, format details, or constraints beyond what the schema provides. Baseline 3 is appropriate.

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?

States a clear verb (Retrieves) and specific resource (Meta campaign performance metrics) with explicit scope (Facebook/Instagram). It distinguishes itself from Google/TikTok siblings by platform, though it doesn't differentiate from get_meta_hourly_performance, which is a plausible confusion given the sibling list.

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?

It advises using list_clients to find client IDs and describes what filters are available, which implies usage. However, it gives no explicit guidance on when to use this tool versus get_meta_hourly_performance or get_meta_opportunity_score, leaving the agent to infer based on granularity.

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