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Pauesome

Ads Analytics MCP

by Pauesome

get_tiktok_campaign_performance

Retrieve TikTok Ads campaign metrics like spend, clicks, conversions, CPA, and ROAS by date range, advertiser, campaign, or status to analyze and audit ad performance.

Instructions

Retrieves TikTok Ads campaign performance metrics for a client. Returns normalized metrics: spend, impressions, clicks, CTR, CPC, CPM, conversions, CPA, conversion value, ROAS. Supports filtering by date range, advertiser IDs, campaign IDs, and campaign status. Data is returned at campaign × day granularity from the TikTok Marketing API /report/integrated/get/ endpoint.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusesNoFilter by campaign status.
client_idNoClient identifier. Use list_clients to see available IDs.
campaign_idsNoFilter to specific campaign IDs. Returns all campaigns if omitted.
advertiser_idsNoOverride the client's default TikTok advertiser ID.
date_range_endNoYYYY-MM-DD. Defaults to today.
date_range_startNoYYYY-MM-DD. 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?

With no annotations, the description carries the full burden. It usefully discloses data granularity (campaign × day) and the upstream endpoint (/report/integrated/get/), but omits pagination behavior, result limits, and whether client_id resolution requires a per-call lookup. Adds some value but leaves meaningful behavioral gaps for a data-retrieval 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?

Three sentences, front-loaded with purpose then return shape then capabilities; the metric enumeration is long but informative for an output-less schema. Little waste overall, though the API endpoint reference borders on internal detail.

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?

No output schema exists, and the description compensates by naming the exact returned metrics and the row granularity. Filtering is covered, but pagination/row limits and behavior when client_id is omitted remain unstated, leaving a modest gap.

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 including defaults and the list_clients pointer. The description merely paraphrases the same filter categories (date range, advertiser IDs, campaign IDs, status) without adding syntax, interaction, or precedence detail. 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 specific verb (Retrieves) and resource (TikTok Ads campaign performance metrics) with the returned metric set enumerated. It also implies differentiation from siblings via the 'campaign × day granularity' note, though it never names the sibling tools it differs from (get_tiktok_hourly_performance, get_tiktok_ad_performance).

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 lists what can be filtered (date range, advertiser IDs, campaign IDs, status) but gives no explicit when-to-use guidance, no when-not-to-use, and no routing to alternative tools when a different granularity is needed. Usage is only implied by the description of capabilities.

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