Skip to main content
Glama
Sign In
YouTube MCP Server

YouTube MCP Server

by danieldoalto
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

videos_getVideo

Retrieve detailed information about a YouTube video by providing its video ID, including specified parts such as statistics or content details.

Instructions

Get detailed information about a YouTube video

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": {
      "videoId": "<videoId>"
    },
    "name": "videos_getVideo"
  }
}

Input Schema

NameRequiredDescriptionDefault
partsNoParts of the video to retrieve
videoIdYesThe YouTube video ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations, the description must fully disclose behavior, but it only says 'Get detailed information' without mentioning that this is a read-only operation, the source API (YouTube Data API v3), or any limitations such as quota costs or required authentication.

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?

The description is a single sentence that is concise and front-loaded, but it sacrifices completeness for brevity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given two parameters and no output schema or annotations, the description is incomplete. It fails to explain the 'parts' parameter, expected output structure, or any preconditions, leaving an AI agent underinformed.

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 coverage is 100% with both parameters described, so the description adds no extra meaning. However, the schema descriptions are vague (e.g., 'Parts of the video to retrieve'), and the tool description does not clarify possible values for 'parts', missing an opportunity to add value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get detailed information about a YouTube video' uses a specific verb ('Get') and resource ('YouTube video'), clearly distinguishing it from sibling tools like videos_searchVideos (which searches) and channels_getChannel (different resource).

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?

No guidance is provided on when to use this tool versus alternatives such as videos_searchVideos or channels_getChannel. The description omits context like 'use for fetching a specific video by ID'.

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

Deploy Server

Other Tools