YouTube transcripts, search, channels, playlists and bulk transcript jobs for AI agents. 14 tools.
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com.transcriptout/youtube-transcript-and-youtube-search is an MCP server that YouTube transcripts, search, channels, playlists and bulk transcript jobs for AI agents. 14 tools. Its tool list has not been published yet over http, requires no API key, and scores 92/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"transcriptout": {
"url": "https://api.transcriptout.com/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_KEY"
}
}
}
}Are you the author?
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Transcripts in five formats, native video and channel search, channel and playlist listings, and background jobs that deliver up to 4,000 transcripts at a time. 14 tools behind one hosted endpoint. Nothing runs on your machine.
Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.
npx -y 'ajv-cli' 2>&1 | head -1 && echo "✓ Server started successfully"
After testing, let us know if it worked:
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No known CVEs.
Checked ajv-cli against OSV.dev.
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Let your AI agent read YouTube.
Transcripts in five formats, native video and channel search, channel and playlist listings,
and background jobs that deliver up to 4,000 transcripts at a time. 14 tools behind one hosted
endpoint. Nothing runs on your machine.
Why · Quick start · Tools · Install · Recipes · Pricing · Errors
Everyone who works with an agent has run this exchange at least once.
You: Summarize this. https://www.youtube.com/watch?v=kCc8FmEb1nY
Agent: I'm not able to watch videos. If you paste the transcript here, I'll gladly help!
The transcript is precisely the thing the agent cannot get on its own. With this server connected, the same message simply resolves.
You: Summarize this. https://www.youtube.com/watch?v=kCc8FmEb1nY
Agent: → get_transcript(video="kCc8FmEb1nY", video_metadata=true) 1 credit
That's "Let's build GPT: from scratch, in code, spelled out" by Andrej
Karpathy, 1:56:20. He starts from an empty file and a bigram model,
derives self-attention step by step, and ends with a working GPT that...
Reading one video is rarely where the job ends. Here is how the three ways of getting YouTube data into an agent actually compare.
| This server | Local yt-dlp / scraper MCP | Google YouTube Data API | |
|---|---|---|---|
| Transcripts | ✅ any public video, 5 formats | ⚠️ blocked on datacenter IPs, breaks when YouTube changes markup | ❌ not served at all |
| Setup | ✅ a URL and an API key | ❌ local install, binaries to keep alive | ❌ Cloud project, OAuth consent screens |
| YouTube search | ✅ native, 1 credit per page | ❌ | ⚠️ 100 quota units per search |
| Channels & playlists | ✅ 100 videos/page, or 500 bare IDs | ❌ one video at a time | ⚠️ quota-metered per item |
| Bulk transcripts | ✅ 4,000 per background job | ❌ | ❌ |
| RAG-ready chunking | ✅ 20-5,000 chars, word-level timestamps | ❌ | ❌ |
| When YouTube changes | ✅ fixed server-side, nothing to update | ❌ you patch and redeploy | ✅ |
| Failed calls | ✅ credits refund themselves | ❌ your retry logic | ⚠️ quota spent anyway |