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YouTube Studio MCP

YouTube Studio MCP

by nelsonrogers
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Revenue report

get_revenue
Read-onlyIdempotent

Extract YouTube Partner Program revenue metrics, RPM, CPM, and top-earning videos for a chosen date range. Track monetization trends and identify high-earning content.

Instructions

Monetization report (YouTube Partner Program channels): estimated revenue, ad revenue, gross revenue, RPM, CPM, playback-based CPM, monetized playbacks and ad impressions, with a trend and the top-earning videos.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_revenue"
  }
}

Input Schema

NameRequiredDescriptionDefault
periodNoNamed date range, Studio-style. Rolling ranges end at the latest complete day of data (analytics lag ~2-3 days; dates are US Pacific). Ignored when start_date is set.last_90_days
currencyNoISO 4217 code, e.g. 'EUR'. Default USD.
end_dateNoCustom range end, YYYY-MM-DD (inclusive). Defaults to the latest complete day.
start_dateNoCustom range start, YYYY-MM-DD. Overrides `period`.
granularityNoBucket size for the trend.month
top_videos_limitNoTop-earning videos to include.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered. The description adds the meaningful constraint that this only applies to YouTube Partner Program channels and that output includes a trend and top-earning videos, but says nothing about analytics lag, currency conversion behavior, or empty/zero-revenue results, which would be the valuable additions here.

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?

One front-loaded sentence with no filler or hedging; the parenthetical scoping clause is well placed. The metric list is long but every item carries selection information, so it earns its length.

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?

An output schema exists, so return-value explanation is not required, and annotations carry the safety profile. What remains missing is any guidance on tool selection among a large analytics sibling set and any note on data lag or zero-data behavior, leaving the definition adequate but incomplete for a 6-parameter reporting tool.

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% and each parameter (period, currency, start/end date, granularity, top_videos_limit) is documented with defaults, formats, and the start_date-overrides-period rule. The description only obliquely references parameters via 'trend' and 'top-earning videos', adding little beyond the schema, so 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?

Names a specific resource: monetization/YouTube Partner Program revenue report, and enumerates the exact metrics returned (estimated revenue, ad revenue, RPM, CPM, monetized playbacks, ad impressions) plus a trend and top-earning videos. That is far more specific than a restated title. It stops short of distinguishing the tool from siblings such as get_metrics_over_time or get_impressions, so a 4 rather than a 5.

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

Usage Guidelines2/5

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

The parenthetical '(YouTube Partner Program channels)' implies a precondition but is not framed as one, and there is no statement of when to use this versus get_metrics_over_time, get_impressions, or get_top_videos, nor any note on data lag or date-range defaults. An agent must infer selection from metric names alone.

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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