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ChristophLanganke

youtube-mcp

get_transcript

Fetch a YouTube video's transcript or subtitles for reading, summarizing, or quoting. Works for any public video without sign-in; accepts a video ID or any YouTube URL.

Instructions

Fetch the transcript/subtitles of a YouTube video for reading, summarizing or quoting. Works for any public video without sign-in. Accepts a video ID or any YouTube URL. Long transcripts are truncated at max_chars — request a later start_seconds to continue.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoPreferred caption language code, e.g. de or en. Defaults to the video's default track.
videoYesVideo ID or URL (watch, youtu.be, shorts, embed)
formatNotext = plain prose (cheapest, best for summarizing); timestamped = [mm:ss] lines for citing momentstext
max_charsNoCharacter budget for the transcript body. Set 0 for no limit.
end_secondsNoOnly include cues at or before this timestamp
translate_toNoMachine-translate the track into this language code, e.g. de. Only for translatable tracks.
prefer_manualNoPrefer human-written captions over auto-generated ones when both exist
start_secondsNoOnly include cues at or after this timestamp
include_metadataNoPrefix the output with title, channel, duration and track info

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations provided, the description carries the behavioral disclosure burden. It discloses the access requirement (no sign-in), the input formats accepted, and the critical truncation behavior: long transcripts are cut at max_chars and can be continued by requesting a later start_seconds. It does not mention error cases or rate limits, but covers the most agent-relevant behaviors.

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 four short sentences, each earning its place: purpose, access scope, accepted input shapes, and truncation behavior. It is front-loaded with the core purpose and contains no filler or repetition.

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 tool's complexity (9 parameters, no annotations, no output schema), the description is admirably complete for invocation purposes. It covers purpose, auth, input, and pagination behavior. It could go further by briefly describing the return shape or error cases, but the schema already documents all parameters and formats.

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. The description adds value beyond the schema by explaining the interaction between max_chars and start_seconds for continuing truncated transcripts, and by clarifying that the tool works for any public video regardless of auth. This extra semantic context justifies a 4.

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 uses a specific verb and resource: 'Fetch the transcript/subtitles of a YouTube video.' It states the intended uses (reading, summarizing, quoting) and the scope (any public video, no sign-in), which distinguishes it from siblings like list_transcript_languages and download_my_caption.

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?

The description gives a clear context for use: works for any public video without sign-in, and accepts a video ID or any YouTube URL. It does not explicitly name sibling alternatives for edge cases like private videos or the user's own captions, so it falls short of full when/when-not guidance.

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