ytfetch-mcp 1.1.0

YouTube transcript MCP server for Claude & ChatGPT. Token-efficient, cached, reliable.

yt-transcript-mcp

YouTube transcripts as token-efficient AI context. One fetch, cached forever.

Works with Claude Desktop, ChatGPT Desktop, Cursor, Windsurf, and any MCP client.

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Why?

When AI browses YouTube for a transcript, it processes the entire page: navigation, ads, recommendations, scripts. That's 75,000–150,000 tokens of noise to extract maybe 6,000 tokens of actual content.

This tool fetches only the transcript.

	Tokens	Speed	Repeat queries
AI browses YouTube	75–150k	20–90s	Same cost every time
yt-transcript-mcp	6–12k	1–3s	Instant (cached)

Once cached, a transcript costs zero tokens to retrieve again. Same content can feed 10 different conversations without a single YouTube request. Less compute, less energy, more output.

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Demo

You say:

Fetch the transcript from https://www.youtube.com/watch?v=dQw4w9WgXcQ

The tool returns:

# Never Gonna Give You Up

source: https://www.youtube.com/watch?v=dQw4w9WgXcQ
channel: Rick Astley
published: 2009-10-25
language: en
segments: 56
metadata_source: oembed+pytubefix
fetched: 2026-08-02

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## Transcript

We're no strangers to love You know the rules and so do I
A full commitment's what I'm thinking of You wouldn't get
this from any other guy...

Clean markdown. Metadata header for context. No HTML, no noise, no wasted tokens.

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Install

One line. No git clone needed.

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "yt-transcript": {
      "command": "uvx",
      "args": ["--from", "git+https://github.com/bjornwalther/yt-transcript", "yt-transcript-mcp"]
    }
  }
}

Restart Claude Desktop. Done.

ChatGPT Desktop

Same config in your Codex MCP settings, or add manually:

Field	Value
Command	uvx (or full path: ~/.local/bin/uvx)
Arguments	--from git+https://github.com/bjornwalther/yt-transcript yt-transcript-mcp

Tip: Find your uvx path with which uvx. Arguments must be separate values, not one string.

Cursor / Windsurf / VS Code

Paste the same JSON block into your MCP server config.

Requires

uv (includes uvx): curl -LsSf https://astral.sh/uv/install.sh | sh

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Features

Local cache. Transcripts stored in ~/.cache/yt-transcript/ (15–50 KB per video). A year of heavy use stays under 25 MB. Second fetch: instant, zero network, zero energy.

Retry with backoff. YouTube rate-limits sometimes. Retries 3x with 3s delays. Output tells you what happened:

note: Retry succeeded (attempt 2/3).

Layered metadata. Title and channel via YouTube oEmbed (fast, no API key). Publish date via pytubefix fallback. Manual overrides always win: pass title, channel, or published directly.

Transparency. Every response shows metadata source, cache status, retry info. No guessing, no silent failures.

Lean code. Minimal dependencies, ~100 lines for the MCP server. Less code = less to break, less energy to run.

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Parameters

Parameter	Description
url	YouTube URL (required, any format)
languages	Language codes, e.g. sv,en (default: sv,en)
include_timestamps	true for [HH:MM:SS] per line
title	Override title
channel	Override channel
published	Override date (YYYY-MM-DD)
bypass_cache	true to force fresh fetch

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CLI

Also works standalone, no MCP client needed:

uvx --from git+https://github.com/bjornwalther/yt-transcript yt-transcript https://youtu.be/ABC123

Saves a .md file to ./transcripts/. Flags: --date, --title, --channel, --lang, --out, --no-clean, --no-cache.

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Roadmap

• Summary mode — condensed output for lower token cost
• Chapter/topic filtering — return only relevant sections
• Token budget (max_tokens) — fit any context window
• Batch URLs — multiple videos in one call
• MCP registry listing

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Support

If this saves you time or tokens:

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MIT © Björn Walther