I turned ChatGPT into a YouTube research agent ๐คฏ
It searched 5 pizza tutorials, read every transcript, compared the methods, built one perfect recipeโand linked its findings to the exact moments in each video.
Hereโs how ๐
Claude can now watch YouTube for you. ๐
@SimunajAdrijan I connected it to TranscriptAPI and turned it into a full YouTube research bot.
Now Claude can:
โ Search YouTube videos
โ Read entire transcripts
โ Compare multiple videos
โ Find exact moments with timestamps
โ Turn hours of content into useful answers
Hereโs exactly how to set it up ๐
https://t.co/ZipnfcmbNN
We Integrated https://t.co/tK0qohGJb4 into @Berrycrawl for YouTube transcripts.
Super easy to integrate, and their caching layer is genuinely unmatched. Takes years to build something like it.
Made zero sense to rebuild this ourselves.
Great products should be built on great infrastructure together ๐ค
Every YouTube video is a blog post, a newsletter, and a Twitter thread waiting to happen.
The text already exists: it's the transcript.
Pull it. Clean it. Restructure it.
One 20-minute video = 3,000+ words of original content for inspiration.
Wrong: "Transcripts are only useful for subtitles."
Transcripts are text. Text is the universal input for LLMs, search engines, analytics, and content tools.
Every YouTube video is a document waiting to be indexed. 800M+ documents. Most untouched.
All of these run on a single endpoint:
GET /youtube/transcript?videoId=VIDEO_ID
49ms median response.
15M+ transcripts processed monthly.
100 free credits to start. No card required.
https://t.co/XbBBCq7Ee7
YouTube has 800 million videos.
Most of them have a transcript.
We analyzed how the top AI builders are using this data.
Most developers are leaving it completely untouched:
Use case 3: Automated course notes.
Index an online course playlist.
Pull all transcripts.
Run each through an LLM.
Output: chapter summaries, key terms, flashcards, and a study guide.
One builder shipped this as a SaaS and charges $12/month.
15M transcripts extracted last month.
Zero headless browsers.
Zero Selenium instances.
Zero puppeteer configs.
Just a GET request and a Bearer token.
YouTube transcript extraction doesn't need to be hard.
Most "YouTube transcript" tools:
โ Break when YouTube updates
โ Require browser automation
โ Rate limited to ~100 requests/day
โ No search, no playlists, no channels
TranscriptAPI:
โ Production-grade REST API
โ 49ms response times
โ Full search, channels, playlists
โ MCP Supported
โ 1K credits/mo for $5
Built for developers ๐ช