LABSCO SUMMARY
A conference, searchable as one corpus.
The interesting unit here is the playlist, not the video. Loading a whole conference track means you can ask what was said about a topic across dozens of talks and get the answer, which no per-video transcript tool can do. The cost is an explicit fill step before the first query — the transcripts and vectors are built once, and the shipped default is a real playlist you can try before pointing it at your own.
What it is
An experimental MCP server that fetches the transcripts of every video in a YouTube playlist, caches them, and puts them in a vector database so an assistant can search across the entire set rather than one video at a time.
What you get
- Transcripts for a full playlist, retrievable through an MCP client
- A transcript cache and vector database filled in one setup step, so searches run locally afterwards
- The playlist URL as an argument, which is how you swap the preloaded KubeCon London 2025 set for your own
Requirements
No account and no key. Python with uv: clone, uv venv, activate it, then uv pip install -e .. Before first use, run uv run server.py with the playlist URL to fill the transcript cache and vector database — that step is what makes the content searchable. The client entry passes the same playlist URL as an argument. The package is playlist-mcp (version 0.1.0).
Setup effort
Build from source — git clone git@github.com:luebken/playlist-mcp.git; cd playlist-mcp
USE CASES
Finding which talk covered a topic
Search across the playlist's transcripts instead of opening videos one at a time.
Catching up on a conference you missed
Load the track's playlist and ask questions across all of its sessions.
Building a searchable archive of a channel's series
Point the setup step at your own playlist URL to fill the cache and vector store with those transcripts.
INSTALLATION
Connect your client
You clone this one yourself.
Server setup
# Clone this repo
git clone git@github.com:luebken/playlist-mcp.git; cd playlist-mcp
# Install python dependencies
uv venv
source .venv/bin/activate
uv pip install -e .
# Fill the transcript cache and vector db.
uv run server.py https://www.youtube.com/playlist?list=PLj6h78yzYM2MP0QhYFK8HOb8UqgbIkLMcMCP Clients
Claude Desktop
{
"mcpServers": {
"playlist-mcp": {
"command": "uv",
"args": [
"--directory",
"<YOUR_PATH_TO_PARENT_PLAYLIST_MCP>",
"run",
"server.py",
"https://www.youtube.com/playlist?list=PLj6h78yzYM2MP0QhYFK8HOb8UqgbIkLMc"
]
}
}
}