youtube-mcp

get_comments

Fetch the most popular comments from a YouTube video to understand audience reactions.

Instructions

Fetches the most popular comments of a YouTube video. Requires YouTube API key.

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": {
      "videoUrl": "<videoUrl>"
    },
    "name": "get_comments"
  }
}

Input Schema

Name	Required	Description	Default
`videoUrl`	Yes	YouTube video URL or video ID
`maxResults`	No	Maximum number of comments to fetch. Default: 20

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Aug 2, 2026

TDQS

A3.5/5.0

Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It mentions the requirement for a YouTube API key, but does not disclose read-only behavior, error handling, rate limits, or what happens when no comments exist. This is minimal disclosure beyond the basic operation.

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 extremely concise, consisting of just two short sentences. It is front-loaded with the core purpose and includes the key prerequisite, with no wasted words.

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?

Given the tool's simplicity, the description covers the main purpose and the API key requirement, but with no output schema or annotations, it does not explain return format or error behavior. It is adequate but leaves some gaps for a tool with no structured output documentation.

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?

The input schema has 100% coverage with both parameters described. The description adds no extra meaning to the parameters, so the baseline of 3 is appropriate since the schema does the heavy lifting.

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 clearly states the tool fetches the most popular comments of a YouTube video, using a specific verb and resource. It is distinct from sibling tools like get_transcript or get_video_info, which serve different purposes.

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?

The description implies usage for retrieving comments but does not explicitly state when to use this tool over alternatives or provide any exclusions. The context is clear enough, but no alternatives or specific when/when-not guidance is given.

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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