YouTube Closed Captions Extractor - Every Caption Track

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Pull the closed captions off any YouTube video - and not just one language. Each available caption track comes back separately with its language, whether it was human-written or auto-generated, and a ready-made WebVTT version, so localisation and accessibility checks stop being manual work.

Pay per delivered transcript. Videos with no captions, private videos and failed videos are never charged.

What it does

Set up to return every caption track a video actually carries, one row per language, each labelled with its language tag and whether it is human-written or auto-generated, and each carrying a finished WebVTT file plus plain text. That makes it a straightforward answer to two questions the usual transcript tools cannot answer: which languages is this video captioned in, and what do those captions say.

This listing is preset to return TEXT + VTT. Switch formats for any of text, SRT or VTT.

Paste anything YouTube gives you

One urls list accepts video, playlist and channel URLs mixed together — no separate actor, no pre-processing. A channel URL expands to its videos, a playlist to its entries, and maxVideosPerSource caps how deep each one goes.

What you get per video

Field	What it is
plainText	the full transcript as clean paragraphs, not caption fragments
segments	the timed segments behind that text
chapters	chapter-grouped segments when the video has chapters — blocks a model can chunk
srt / vtt	real subtitle files, when you ask for those formats
language, availableLanguages, isAutoGenerated	which track you got, what else exists, and whether it was machine-made
videoId, title, channel, durationSeconds, uploadDate, url	the video's own metadata

Caption fragments are stitched into sentences and paragraphs before delivery, so the output is readable — and chunk-ready for a RAG or search pipeline — instead of a wall of 2-second lines.

Freshness: re-run without re-paying

Set onlyNewVideos and a re-run skips every video already delivered under the same stateLabel. Point it at a channel, schedule it weekly, and you pay only for what is new.

Languages

Ask for specific languages, or set allLanguages to take every transcript track a video publishes. Where a video has no captions at all, the row comes back labelled — never guessed, never silently dropped.

Pricing

$3.00 per 1,000 transcripts. One price, every plan tier, no hidden multiplier.

Free: videos with no captions, private or removed videos, and failed fetches. You are charged only for a transcript you actually receive. Cap any run with maxVideosPerSource, or set a maximum cost on the run itself.

Use it from anywhere

curl -X POST "https://api.apify.com/v2/acts/vonsensey~youtube-closed-captions-extractor/run-sync-get-dataset-items?token=YOUR_TOKEN" \
  -H 'Content-Type: application/json' \
  -d '{"urls":["https://www.youtube.com/watch?v=jNQXAC9IVRw"]}'

from apify_client import ApifyClient
client = ApifyClient("YOUR_TOKEN")
run = client.actor("vonsensey/youtube-closed-captions-extractor").call(run_input={
    "urls": ["https://www.youtube.com/watch?v=jNQXAC9IVRw"],
})
for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(row.get("title"), "-", (row.get("plainText") or "")[:120])

Also available through the Apify integrations for n8n, Make and Zapier, and via MCP for AI agents.

Legal

Unofficial tool. Not affiliated with, endorsed by, or sponsored by YouTube or Google. "YouTube" is a trademark of Google LLC. Reads publicly available caption tracks only — no login, no DRM circumvention, no private or unlisted content.

The rest of the family

• YouTube Transcript Scraper — RAG-Ready
• YouTube Transcript API - Bulk Video Transcripts, Fast
• YouTube Subtitle Downloader - SRT & VTT Subtitle Files
• YouTube Shorts Transcript Scraper - Bulk Shorts to Text
• YouTube Video Transcription - Video to Text at Scale
• YouTube Channel Transcript Scraper - Whole Channel to Text
• YouTube Playlist Transcript Scraper - Whole Playlist to Text
• YouTube Transcript RAG Dataset Builder - Chunk-Ready Text

Issues and requests go in the Issues tab — first response within 24 hours.

Use it from n8n, MCP, the API or a schedule

Built to be called by a workflow, not only from the Store form. The Actor is vonsensey/youtube-closed-captions-extractor; every snippet below sends {}, which runs the defaults shown on the form — replace it with your own input.

n8n

Install the Apify community node (@apify/n8n-nodes-apify under Settings → Community Nodes, or search "Apify" on n8n Cloud). Add Apify → Run Actor with Actor vonsensey/youtube-closed-captions-extractor and your input JSON, then Apify → Get Dataset Items on the run's defaultDatasetId and pipe the rows anywhere. For scheduled runs, the On new Apify Event trigger fires when a run of this Actor finishes.

MCP (Claude, Cursor, VS Code, any MCP client)

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=vonsensey/youtube-closed-captions-extractor",
      "headers": {
        "Authorization": "Bearer <YOUR_APIFY_TOKEN>"
      }
    }
  }
}

Your agent then calls vonsensey/youtube-closed-captions-extractor as a tool with the same input the form takes and reads the dataset back.

REST API (one call, rows in the response)

curl -X POST "https://api.apify.com/v2/acts/vonsensey~youtube-closed-captions-extractor/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" -d '{}'

Python

from apify_client import ApifyClient
client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("vonsensey/youtube-closed-captions-extractor").call(run_input={})
for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(row)

JavaScript

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('vonsensey/youtube-closed-captions-extractor').call({});
const { items } = await client.dataset(run.defaultDatasetId).listItems();

Make, Zapier, LangChain, CrewAI

The Apify app in Make and Zapier has a Run an Actor module: pick vonsensey/youtube-closed-captions-extractor. In LangChain and CrewAI the Apify tool wrappers take the same Actor id. A daily schedule needs nothing but the Console: Schedules → Create → this Actor → cron, and the dataset fills on its own.

Run it without configuring anything — Extract the closed captions of a YouTube video, a ready-made example you can start as-is or copy.

Use cases

• Build a RAG corpus. Turn a channel, playlist or URL list into chunk-ready paragraphs with the source video and timestamp on every row — ready to embed.
• Repurpose long video. Pull the spoken text of a talk or podcast and turn it into a post, a newsletter or a clip list without watching it.
• Search what was said. Make a back catalogue greppable: find every mention of a product, a name or a claim across hundreds of videos.
• Keep a corpus fresh. Schedule it and re-runs skip videos already delivered, so you pay for new material only.

Run it on a schedule

A one-off pull answers a question; a schedule answers it every day without you. Open Schedules in the Apify Console, point a cron at this Actor, and the dataset keeps filling on its own — no server, no cron box, no babysitting. Everything here is built to be re-run: you are billed per transcript delivered, and the FAQ below says exactly what a scheduled run that finds nothing new costs.

FAQ

Do I need a YouTube API key?

No. No key, no login, no OAuth and no YouTube quota to manage — you give it a URL and it returns text.

Can I export transcripts to CSV, JSON or Excel?

Yes. Every run writes a dataset you can export in one click from the Console, or pull straight from the API in JSON, CSV, XLSX or JSONL.

What happens to a video with no captions?

It comes back as a free row that says so, rather than failing the run. You are never charged for a video that returned no transcript.

Can I transcribe a whole channel or playlist at once?

Yes — pass the channel or playlist URL and it walks the uploads for you. There are dedicated Actors in this suite for both.

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Something wrong, or a field you need that is missing? Open an issue on the Issues tab — it is read and it gets fixed. If this saved you time, a rating on the Store page helps the next person find it.