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YouTube MCP Server

YouTube MCP Server

by a-shipilo
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

analytics

Read-only

Generate YouTube performance reports for a channel or video to track views, traffic sources, retention, and demographics. Data may be delayed 2-3 days.

Instructions

Готовый отчёт YouTube Analytics по каналу или одному видео. Данные отстают на 2–3 дня.

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": {
      "report": "<report>"
    },
    "name": "analytics"
  }
}

Input Schema

NameRequiredDescriptionDefault
reportYesoverview — итоги за период; daily — по дням; top_videos — лучшие видео периода; traffic_sources — откуда приходят просмотры; search_terms — поисковые запросы YouTube, по которым находят видео; retention — кривая удержания (нужен video_id); geography — страны; devices — устройства; demographics — возраст и пол
end_dateNoYYYY-MM-DD включительно; по умолчанию сегодня
video_idNoОдно видео; без него — весь канал
start_dateNoYYYY-MM-DD; по умолчанию дата публикации видео или 28 дней назад для канала

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already cover readOnlyHint=true and openWorldHint=true, so the safety profile is clear. The description adds a valuable behavioral detail beyond annotations: data lags 2–3 days, which is critical for interpreting analytics results. It does not discuss auth or rate limits, but that is a minor gap given the annotation coverage.

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?

The description is two short sentences, front-loading the tool's purpose and then adding the important data-freshness caveat. Every sentence earns its place with no redundancy or filler.

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?

Given the rich input schema with full parameter descriptions, an existing output schema, and annotations that cover safety and open-world behavior, the description provides enough context for an agent to call the tool correctly. The only missing piece is explicit routing vs analytics_query, which is a minor 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 four parameters, including the report enum values and date/video semantics. The description adds no additional parameter meaning beyond what the schema provides, so the baseline of 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?

The description clearly states the tool returns a ready-made YouTube Analytics report for a channel or a single video, giving a specific resource and scope. It implicitly distinguishes from the sibling analytics_query through the word 'готовый' (ready-made), but does not explicitly name or contrast with that alternative.

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?

There is no explicit guidance on when to use this tool versus alternatives like analytics_query. The description only states what it provides; it does not mention when-not-to-use, prerequisites, or which sibling to choose for custom queries.

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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