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youtube_captions

Fetch auto-generated or human captions from a YouTube video by its 11-character ID and language code. Returns timed caption cues with text, start time, and duration.

Instructions

Retrieve auto-generated or human captions. Returns the caption cues for a YouTube video by its 11-character video id, in the language given by lang (ISO 639-1, default en). Each cue has its text, start time and duration. Works for both auto-generated and human-written captions.

Input Schema

NameRequiredDescriptionDefault
idYesYouTube video ID (11-character code)
langNoCaption language code (ISO 639-1), defaults to **en**

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.2/5.0
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 does disclose the return shape (cues with text, start time, duration) and the default language behavior, which is useful. It omits failure modes (captions disabled/unavailable), auth, and rate limits, leaving meaningful gaps for a no-annotation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose, but the 'auto-generated or human captions' idea is stated twice (opening sentence and closing sentence), making the last sentence largely redundant. Otherwise compact.

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?

With no output schema, the description usefully explains the return format and the per-cue fields, plus language defaulting. Adequate for a simple 2-param retrieval tool, though it could note behavior when no captions exist.

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 both parameters (id, lang) are already documented. The description restates the 11-character id and ISO 639-1 lang default without adding syntax, validation, or edge-case meaning beyond the schema. 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 clear verb+resource ('Retrieve ... captions') and specifies the input (video id) and output type. However, it does not differentiate from near-identical siblings like youtube_transcript or youtube_transcript_languages, so an agent can't tell which to pick without opening schemas.

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 description gives no when-to-use guidance and never names youtube_transcript or youtube_transcript_languages as alternatives. The only usage hint is the implicit note that it works for both auto-generated and human captions.

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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