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YouTube Transcript API — Melchior Labs
x402
YouTube Transcript API — Melchior Labs is a paid API for AI agents from transcript.melchiorlabs.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).
Fetches structured transcripts from public YouTube videos, returning full text, timestamped chunks, and citation URLs, billed per request via x402.
Price / call$0.01
Success—
StatusUnknown
How this service works
Pay per request for structured YouTube transcripts, lexical passage search, chunks, and timestamp citations over x402.
Output
Returns a JSON object containing: full transcript text with language and source info (manual vs auto-generated), an array of timestamped chunks each with start/end seconds and a citation URL deep-linking to that moment in the video, video metadata (title, duration, ID), and usage stats (character count, estimated tokens, chunk count, cache status).
Example use cases
Research summary from lecture video
“Pull the transcript from this MIT lecture on YouTube — https://www.youtube.com/watch?v=example123 — in English with timestamp citations, so I can summarize the key points by section.”
Podcast episode search and quote retrieval
“Get the full chunked transcript from this podcast episode on YouTube — https://youtu.be/abc456XYZ — and break it into 2400-character segments so I can search for where they discuss climate policy and pull an exact quote with a timestamp link.”
Multilingual content extraction
“Fetch the Spanish captions from this YouTube video at https://www.youtube.com/watch?v=es789example and give me the complete transcript text along with timestamped chunks, preferring manually created captions if available.”
Technical details
Endpoint
POSThttps://transcript.melchiorlabs.com/v1/youtube/transcript?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need structured, agent-ready YouTube transcripts with timestamped chunks and citation URLs in a single pay-per-call request, especially when integrating into LLM pipelines that require grounded references back to specific video moments. Prefer it over generic scraping when you need clean text segmentation with configurable chunk sizes and built-in token usage estimates.
Side effects
- Video is private or age-restricted — no transcript returned
- No captions available in requested language — error or fallback to auto-generated
- Invalid or non-YouTube URL format — validation error
- Video has disabled captions entirely — no transcript available
- Network timeout fetching captions from YouTube — request error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| url | string | Public youtube.com or youtu.be video URL |
| language | string | Caption language code, such as en or es |
| includeText | boolean | |
| preferManual | boolean | |
| includeSegments | boolean | |
| maxChunkCharacters | integer |
Output
Schema · Response
{
"type": "json",
"example": {
"usage": {
"cache": "miss",
"characters": 4200,
"chunkCount": 2,
"estimatedTokens": 1050
},
"video": {
"id": "dQw4w9WgXcQ",
"url": "https://www.youtube.com/watch?v=dQw4w9WgXcQ",
"title": "Video title",
"durationSeconds": 213
},
"chunks": [
{
"text": "Agent-ready context...",
"index": 0,
"citation": {
"url": "https://www.youtube.com/watch?v=dQw4w9WgXcQ&t=0s",
"label": "0:00–0:35"
},
"endSeconds": 35,
"startSeconds": 0
}
],
"requestId": "0b0ef10e-ff50-4a45-9c4e-b7344aa93f63",
"transcript": {
"text": "Transcript text...",
"source": "manual",
"language": "en",
"segmentCount": 42
}
}
}Tags
x402
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