Model Context Protocol
Connect this MCP server once, then ask your AI to read, summarize, translate or quote any YouTube video. Or ask it to research a whole topic: it searches YouTube, finds what the videos say, checks the comments, and tells you what several sources agree on. No copy-paste, no browser tab.
https://youtube-transcript.ai/mcp?key=YOUR_KEY
Replace YOUR_KEY with your free API key. Create one here: sign in with Google, 10 requests a day free.
Using Claude Code, Cursor or Codex? Copy the setup instructions and paste them into your agent. It can add the server to its own configuration.
Or view the instructions as plain text.
A free API key covers 10 requests a day: plenty for reading a few videos. Researching a topic takes more, and Pro is 1,000 a day for $120 a year.
A hardened fetch pipeline with proxy fallback gets transcripts even on videos that block typical scrapers, so your AI rarely comes back empty-handed.
Pick any available caption track by language code — English, 中文, Español, 日本語 and more — or let it choose the default.
Plain-text output with title and metadata. Drop a link mid-conversation and your model just reads it. Multi-hour videos come back in parts, so nothing gets cut off.
Search YouTube, jump to the exact moment a video mentions something, skim several transcripts at once, read top comments and follow a channel. Or full-text search about 100 million spoken sentences from 425,000+ videos, with typically 1 to 8 million new sentences added every day, and see which videos and channels talk about a topic the most.
Reading one transcript answers one video. These tools let your AI work through dozens and report back with sources.
search_youtube_videos finds videos on a topic, with channel, views and length. Filter out the short and the obscure.find_in_transcript returns only the passages that mention your keywords, each with a timestamp and a link to that moment.get_transcripts_batch reads up to 5 videos in one call, each cut to the length you choose.get_video_comments reads the top comments, where viewers say what worked for them.list_channel_videos lists the videos of a channel or playlist, 50 at a time, and pages on to the first 500.get_account_status shows your plan, daily quota and how many requests you have left. It is free and uses no quota, so your AI can check before a big job.And a library of what people say, with full-text search: about 100 million spoken sentences from 425,000+ English videos, and typically 1 to 8 million new sentences added every day:
search_spoken_words finds the sentences where people say something, with a link to that moment in the video.get_spoken_context reads the lines before and after a moment.rank_videos_by_topic and rank_channels_by_topic show which videos and channels talk about a topic the most.spoken_mentions_over_time counts mentions by day, week or month, to see whether a topic is rising.Try asking:
Research how people improved their English speaking. Search YouTube in English and Chinese, look at videos from people telling their own story, find what methods they used and how long it took, check the comments, and tell me which methods several unrelated people agree on.
A research run like this takes about 30 to 40 requests: a few searches, then a look inside each promising video. The free key's 10 a day covers a quick look. Pro gives you 1,000 a day for $120 a year, enough to run several full research sessions a day without counting.
get_youtube_transcript, reads the full transcript, and answers from it.The server needs a key to fetch transcripts. Create a free key (Google sign-in, about a minute) and put it in the connector URL below in place of YOUR_KEY. Already connected without a key? Remove the connector and add it again with the new URL.
youtube-transcript.ai and the URL to https://youtube-transcript.ai/mcp?key=YOUR_KEY, then save.get_youtube_transcript tool automatically.youtube-transcript.ai and the server URL to https://youtube-transcript.ai/mcp?key=YOUR_KEY (transport: Streamable HTTP).https://youtube-transcript.ai/mcp and ask Muse to connect this MCP server. It sets up the connection for you.Run this once in a terminal. --scope user makes the server available in every project.
claude mcp add --transport http --scope user youtube-transcript \ https://youtube-transcript.ai/mcp \ --header "Authorization: Bearer YOUR_KEY"
Add the server to ~/.cursor/mcp.json, or to .cursor/mcp.json inside one project.
{
"mcpServers": {
"youtube-transcript": {
"url": "https://youtube-transcript.ai/mcp",
"headers": { "Authorization": "Bearer YOUR_KEY" }
}
}
}
Add the server to ~/.codex/config.toml.
[mcp_servers.youtube-transcript]
url = "https://youtube-transcript.ai/mcp"
http_headers = { "Authorization" = "Bearer YOUR_KEY" }
Give it https://youtube-transcript.ai/mcp?key=YOUR_KEY as a remote Streamable HTTP server. The key can go in the URL, as here, or in an Authorization: Bearer header.
https://youtu.be/… in 5 bullets.”<link>? Quote the exact lines.”The same key works over plain HTTPS from Python, JavaScript, n8n or Make. See the YouTube Transcript API.
No AI client needed — paste any link into the free web extractor.