tldw-mcp
MCP server that extracts YouTube video transcripts (including metadata) as Markdown, enabling AI to summarize and discuss video content without watching it.
README
tldw-mcp — Too Long; Didn't Watch
An MCP server that turns any YouTube video into a clean Markdown transcript (plus metadata), ready for an AI to summarize and discuss. No more sitting through a 1-hour video to find out if it was worth it — fetch the transcript, let your AI summarize it, then chat about it.
Built with FastMCP (Python), served over Streamable HTTP, and exposed remotely through a Cloudflare Tunnel so you can use it from ChatGPT, Claude, your phone, or anywhere.
Tools
| Tool | Input | Output |
|---|---|---|
get_transcript |
url, lang?, include_timestamps? |
Markdown: frontmatter (title, channel, duration, date…) + transcript |
get_video_info |
url |
Markdown: metadata + description (no transcript) |
lang— preferred caption language (en,fr, …). If omitted: manual subs first, then the video's original language, then English.include_timestamps— prefix each line with[mm:ss].
No video is ever downloaded — only the caption track (official subtitles preferred, auto-generated as fallback) via yt-dlp.
How it works
client (ChatGPT / Claude / phone)
│ HTTPS https://<host>/<secret-path>/mcp
▼
Cloudflare Tunnel ──► 127.0.0.1:8765 (uvicorn)
server.py (FastMCP)
└─ yt-dlp ──(proxy)──► YouTube captions
Auth = a secret URL path. The MCP endpoint is mounted at an unguessable path
(MCP_PATH); any other path returns 404. Simple, and works with clients that can't send
custom headers. The server binds only to 127.0.0.1 — it is never exposed directly.
Local run
python3 -m venv .venv
.venv/bin/pip install -r requirements.txt
MCP_PATH=/mcp PORT=8765 .venv/bin/python server.py
Configuration (env vars)
| Var | Default | Purpose |
|---|---|---|
MCP_PATH |
/mcp |
Secret URL path the MCP endpoint is mounted at |
PORT |
8765 |
Local port (bind is always 127.0.0.1) |
YTDLP_BIN |
yt-dlp |
Path to the yt-dlp binary |
YTDLP_PROXY |
(none) | HTTP proxy for yt-dlp and caption download (http://user:pass@host:port) |
Datacenter IPs are blocked by YouTube ("Sign in to confirm you're not a bot"). When deploying on a VPS/cloud server, set
YTDLP_PROXYto a residential proxy or it won't work.
Deploy on a server (systemd + Cloudflare Tunnel)
- Copy
server.py+requirements.txtto the server (e.g./root/youtube-mcp/), create the venv, install deps. - Make sure
yt-dlpis installed (/usr/local/bin/yt-dlp). - Install the systemd service (generates a random secret path, restarts on crash/reboot):
export YTDLP_PROXY='http://user:pass@host:port' # if your server IP is blocked bash deploy-setup.sh - Install cloudflared and connect a tunnel whose public hostname points to
http://localhost:8765(HTTP, not HTTPS):cloudflared service install <YOUR_TUNNEL_TOKEN> - Your MCP URL is
https://<your-hostname>/<secret-path>/mcp(the secret path is printed bydeploy-setup.shand stored in.mcp_path).
Connect a client
- Claude Code:
claude mcp add --transport http tldw https://<host>/<secret>/mcp - ChatGPT (Plus/Pro): Settings → Connectors → developer mode → Add MCP server → paste the URL (auth: None).
- Claude Desktop: Settings → Connectors → add a custom connector with the URL.
Test
MCP_URL="https://<host>/<secret>/mcp" bash test-public.sh
License
MIT
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