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YouTube Transcript AI

by ai.youtube-transcript
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get_youtube_transcript

Fetch the full text transcript of a YouTube video. Accepts a YouTube URL (watch, youtu.be, shorts, embed) or a bare 11-character video ID, and returns the transcript as plain text with title and metadata. Optionally pass a BCP-47 language code to select a specific caption track. Very long transcripts (multi-hour videos) come back in parts of up to 120,000 characters: when there is more, the result ends with a note giving the offset to pass on the next call.

Input Schema

NameRequiredDescriptionDefault
langNoOptional BCP-47 language code, e.g. "en", "zh-CN", "es". Omit for the default track.
videoYesYouTube video URL or 11-character video ID
offsetNoOptional. Character position to continue a long transcript from. Use the value given in the note at the end of the previous part. Omit to start from the beginning.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / offset
      Added value: +{
+  "description": "Optional. Character position to continue a long transcript from. Use the value given in the note at the end of the previous part. Omit to start from the beginning.",
+  "minimum": 0,
+  "type": "integer"
+}
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the return shape (plain text with title and metadata) and the important pagination behavior for multi-hour videos, including the 120,000-character part size and the offset handoff mechanism. It omits failure modes (no captions, private/removed video), which is the main remaining gap.

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?

Three sentences, front-loaded with the core capability, then input forms, then the pagination caveat. Every sentence earns its place with no 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?

No output schema exists, so the description must cover return values, and it does (plain text transcript plus title/metadata, paginated with offsets). The only meaningful omission is error behavior when no caption track exists or the video is unavailable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds value by enumerating the URL/ID forms the 'video' parameter accepts and explaining the offset continuation workflow end-to-end. It reinforces rather than merely repeats the schema.

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?

States a specific verb (Fetch) and resource (full text transcript of a YouTube video), plus the exact inputs accepted. An agent knows unambiguously what the tool returns.

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

Usage Guidelines4/5

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

Explains accepted input formats (watch, youtu.be, shorts, embed, bare 11-char ID) and the optional language selection, giving clear context for invocation. There is no explicit when-not guidance, but with no sibling tools and a single obvious purpose, little more is needed.

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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