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🎥 YouTube Transcript & Subtitles Scraper: Pay-Per-Video MCP API

Scrape YouTube transcripts, subtitles, and captions in bulk at near-free pay-per-video rates. Built for MCP clients (Claude, Cursor, VS Code, ChatGPT), AI agents, content pipelines, and SEO research. Works with standard videos, YouTube Shorts, and every URL format.

💡 Pricing: $0.0001 per video transcribed, about $0.10 per 1,000 videos. Tiny per-run startup + per-result fees ($0.00001 each, set by Apify). No subscription, no proxy fees.

Example code (Python): https://github.com/johnisanerd/Apify-Youtube-Transcripts-API

⚡ What you get back

For every video, the dataset receives:

• non_timestamped - full transcript text, ready for LLMs.
• timestamped - every snippet with text, start, and duration in seconds.
• language, language_code, is_generated, is_translatable, translation_languages.
• total_seconds - video duration.
• video_id, url, success, timestamp.
• On failure: structured error, error_message, error_type (no crash; the run continues).

🎯 Use cases

• LLM training data - bulk-collect transcripts for fine-tuning or RAG.
• AI agents that watch YouTube - let Claude or Cursor pull a transcript on demand via MCP.
• Content repurposing - turn videos into blog posts, summaries, or social clips.
• SEO research - mine transcripts for keywords, topics, and competitor analysis.
• Podcast & video search - index thousands of videos by their actual spoken content.

🤖 Use with MCP (Claude, Cursor, VS Code, ChatGPT)

This Actor is callable as a tool from any Model Context Protocol client. The Apify MCP server exposes every Actor on the store: no installation, no separate package.

Step 1: Get an Apify API token

Grab a token from your Apify account → Integrations.

Step 2: Connect your MCP client

Claude Desktop / Claude Code: edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
"mcpServers":{
"apify":{
"url":"https://mcp.apify.com",
"headers":{"Authorization":"Bearer YOUR_APIFY_TOKEN"}
}
}
}

Cursor: add .cursor/mcp.json in your project (or ~/.cursor/mcp.json globally):

{
"mcpServers":{
"apify":{
"url":"https://mcp.apify.com",
"headers":{"Authorization":"Bearer YOUR_APIFY_TOKEN"}
}
}
}

VS Code: add .vscode/mcp.json:

{
"mcpServers":{
"apify":{
"url":"https://mcp.apify.com",
"headers":{"Authorization":"Bearer YOUR_APIFY_TOKEN"}
}
}
}

ChatGPT / web-only clients: use the hosted Apify Tester MCP Client in the browser.

Step 3: Ask your agent

Once connected, prompt naturally:

"Use Apify to get the transcript of https://www.youtube.com/watch?v=dQw4w9WgXcQ"

"Pull YouTube transcripts for these three URLs and summarize each: …"

"Find the YouTube transcript scraper on Apify and run it for this Shorts URL."

Your client will discover this Actor via the search-actors tool, register it as a callable function, and feed the transcript back into the conversation.

Full reference: Apify MCP integration docs · MCP server source.

🔧 Input

Single video

{"youtube_url":"https://www.youtube.com/watch?v=p8gV_7zFN44"}

Batch (processed in parallel)

{
"youtube_url":[
"https://www.youtube.com/watch?v=5kcaHAuGxmY",
"https://www.youtube.com/watch?v=p8gV_7zFN44",
"https://www.youtube.com/shorts/s4UkCaf_scs"
]
}

💡 Pro tip for large batches. For batches of more than ~25 URLs, open Advanced settings on the run page and increase the Timeout before clicking Start, or split the input across multiple runs. Failed or timed-out videos are still recorded in the dataset (with success: false and an error_message), so you can always retry only the missing ones.

📤 Example output

{
"url":"https://www.youtube.com/watch?v=p8gV_7zFN44",
"video_id":"p8gV_7zFN44",
"language":"English",
"language_code":"en",
"is_generated":false,
"is_translatable":true,
"translation_languages":["es","fr","de"],
"total_seconds":4782.52,
"timestamped":[
{"text":"Hello and welcome to this video","start":0.08,"duration":3.5}
],
"non_timestamped":"Hello and welcome to this video...",
"timestamp":"2026-05-11T10:30:00",
"success":true
}

💰 Pricing

Total cost examples (typical 1-video run = setup + 1 video + 1 dataset item):

Unlike actors that charge per second of video, this one charges per video: a 5-hour lecture costs the same as a 60-second Short. No subscription, no proxy fees. Failed videos and videos with no transcript are not charged.

🚀 Quickstart

1. Open this Actor on the Apify store.
2. Paste a YouTube URL into youtube_url (or an array of URLs).
3. Click Start. Results appear in the dataset within seconds.

Prefer the API? Every Actor on Apify has an API endpoint and can be called from any language, scheduled, or wired into webhooks.

❓ FAQ

What if the video has no transcript? The Actor records an error entry in the dataset (success: false, error_message: …) and moves on to the next URL. You are only charged for successful transcriptions of the requested videos.

Does it work for YouTube Shorts? Yes. https://www.youtube.com/shorts/VIDEO_ID works out of the box, as do youtu.be/, /embed/, and m.youtube.com formats.

Can I call this from an AI agent? Yes, that is the primary design goal. See the Use with MCP section above for Claude, Cursor, VS Code, and ChatGPT setup.

What about translation? The output includes is_translatable and a list of translation_languages available for each transcript. Translation itself is not performed by this Actor; pair it with your favorite LLM (or another Apify Actor) for translation.

Why is this so much cheaper than other YouTube transcript scrapers? This is a loss-leader: built for adoption, not margin. The actor uses YouTube's own caption tracks via a free open-source library, so the marginal cost is near zero.

🔗 Links

• Actor on Apify Store
• Apify MCP integration docs
• Model Context Protocol
• Apify platform docs

Featured Tasks

Ready-to-run examples that show this API solving a specific problem. Each opens its own setup so you can run it on your account in one click.

• Get YouTube transcripts in Claude Code via MCP - pull any video's transcript straight into Claude Code (free trial available) through MCP, with timestamped and plain text output.
• Use YouTube transcripts in Claude Cowork via MCP - fetch transcripts inside Claude Cowork (free trial available) as an MCP plugin for research and document workflows.
• Download a batch of YouTube transcripts in bulk - transcribe a whole list of videos in one run, one dataset row per video with language metadata.

Last Updated: 2026.06.19