youtube-mcp
Fetches video transcripts, playlist contents, and metadata (title, channel, duration, publish date, views, likes, description, caption languages) from YouTube.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@youtube-mcp Get the transcript of this YouTube video"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
youtube-mcp
A small MCP server that lets a model read public YouTube data. Three tools, no API key, nothing clever:
tool | what you get |
| what is said in a video, as plain text, optionally trimmed to a time window, plus which language it came back in |
| the videos in a playlist, in order |
| title, channel, duration, publish date, views, likes, description, caption languages |
That is the entire surface. The server fetches, checks the link, trims by timestamp and returns. Summarising, searching and ranking are the calling model's job, not this server's.
Requirements
Python 3.12 or newer
uv for the short path, though plain pip is fine
Related MCP server: YouTube MCP
Install
git clone https://github.com/chiekh-a/youtube-mcp.git
cd youtube-mcp
uv venv
uv pip install -e ".[dev]"With pip instead:
python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"Configuration
Copy the example file and fill in whatever you need:
cp .env.example .envAll of it is optional. With an empty .env the server still runs, it just talks
to YouTube directly from wherever it happens to be.
variable | default | what it does |
|
| the switch that turns the proxy on |
| unset | proxy endpoint, credentials included |
|
|
|
|
| bind address, http only |
|
| bind port, http only |
| unset | where the server is reachable, used for the icon URL |
PUBLIC_BASE_URL is only worth setting if you deploy somewhere that is not
Railway. Railway publishes the domain itself and the server picks it up. Leave
it unset over stdio, where the icon travels inline instead.
Why the proxy exists
YouTube is aggressive about blocking datacenter IP ranges. On your own machine you will usually be fine without a proxy. On a server (Railway, a VPS, CI) the transcript requests start coming back as bot checks fairly quickly, and pointing them at a residential proxy is the fix.
Both variables have to be set before anything is routed. A URL sitting in the
environment with YOUTUBE_USE_PROXY=false is ignored, which makes it easy to
flip on and off without editing config.
The proxy URL contains a password. It is never logged, and .env is gitignored.
Please keep it that way.
Run it
Over stdio, which is what a desktop MCP client expects:
uv run python -m youtube_mcpOver HTTP, for when the server lives somewhere else:
uv run python -m youtube_mcp --transport http --host 0.0.0.0 --port 8000The endpoint is /mcp, so a local server answers at
http://127.0.0.1:8000/mcp. Leave the trailing slash off. A URL ending in
/mcp/ gets redirected, and the redirect loses the session header, so the
client fails with a confusing 400.
Flags: --transport, --host, --port, --log-level. Logs always go to
stderr, because stdout belongs to the MCP protocol.
Connect a client
Local, over stdio
Drop this into claude_desktop_config.json, or .mcp.json for Claude Code, and
point the path at your checkout:
{
"mcpServers": {
"youtube": {
"command": "uv",
"args": [
"--directory",
"/absolute/path/to/youtube-mcp",
"run",
"python",
"-m",
"youtube_mcp"
],
"env": {
"YOUTUBE_USE_PROXY": "false"
}
}
}
}If you would rather not go through uv, call the venv's Python directly:
{
"mcpServers": {
"youtube": {
"command": "/absolute/path/to/youtube-mcp/.venv/bin/python",
"args": ["-m", "youtube_mcp"]
}
}
}Claude Code can skip the file editing entirely:
claude mcp add youtube -- uv --directory /absolute/path/to/youtube-mcp run python -m youtube_mcpRemote, over HTTP
Once it is deployed somewhere:
{
"mcpServers": {
"youtube": {
"type": "http",
"url": "https://your-app.up.railway.app/mcp"
}
}
}No trailing slash on that URL, for the reason above.
Deploy to Railway
There is a Dockerfile and a railway.json in the repo, so Railway needs very
little from you.
Push the repo to GitHub.
In Railway, create a project from the repo. It finds the Dockerfile by itself.
Under Settings, Variables, add:
MCP_TRANSPORT=httpMCP_HOST=0.0.0.0YOUTUBE_USE_PROXY=trueYOUTUBE_PROXY_URL= your proxy endpoint
Generate a domain under Settings, Networking.
PORT comes from Railway, so leave it alone.
From the CLI instead:
railway login
railway init
railway up
railway domainTwo things to keep in mind about a public deployment. The HTTP endpoint has no
auth on it, so anyone holding the URL can spend your proxy quota. And a hosted
IP will run into YouTube's bot checks without a residential proxy, which is the
whole reason YOUTUBE_USE_PROXY is there.
How it behaves
Small decisions that occasionally surprise people, all of them on purpose:
Only
https://links, and only onyoutube.com,m.youtube.comoryoutu.be.Shorts are turned away. Pass a regular video link.
Captions are tried in this order and the first hit wins: en, ar, fr, es, de, it, pt, ru, zh. If a video has none of those, you get whatever it does have rather than an error, since the model reading it can translate. The response says which language turned up, and whether a human wrote the captions or speech recognition did.
Trimming is an overlap test, not a containment test. A caption line that begins before
start_secondsbut is still being spoken at that moment is kept whole, because half a sentence is worth less than a slightly wider clip.start_secondshas to be strictly smaller thanend_seconds. Equal values are an error, and it is caught before any request goes out.A video with no captions in a supported language is an error. A time window that lands past the end of the video is simply an empty result.
Only text comes back, never timestamps. They are dead weight in a context window.
youtube_playlistalso accepts a watch link that happens to be playing inside a playlist, since it carries the samelist=id.
When something breaks
"Sign in to confirm you're not a bot", or "YouTube is blocking requests from
your IP". The host is on an IP range YouTube does not trust, which is normal
for any cloud provider. Set YOUTUBE_USE_PROXY=true with a working residential
proxy. Playlist listing often keeps working while transcripts and video facts
fail, so a partial outage like that is usually this.
Tunnel connection failed: 407 Proxy Authentication Required. The proxy is
reachable and it turned your credentials down. Check the username and password,
and check whether the provider expects the client IP to be allowlisted first.
The scheme on the proxy URL is not the problem, http:// and https:// behave
the same here.
A 400 from the HTTP endpoint straight after connecting. The client URL ends
in /mcp/. Drop the trailing slash.
Nothing at all over stdio. Something wrote to stdout. Only this server's own
logging is careful about that, so a stray print in your own changes is the
usual culprit.
Tests
uv run pytestNothing in the suite touches the network. An autouse fixture in
tests/conftest.py swaps both clients for tripwires that raise on contact, so a
forgotten stub fails loudly instead of quietly making live requests.
Layout
youtube_mcp/
__main__.py flags, transport choice, start
server.py the FastMCP instance and the three tools
links.py parsing YouTube URLs into ids
captions.py caption fetching and the time window
catalog.py yt-dlp: playlists and video facts
schemas.py what the tools return
settings.py the only module that reads the environment
errors.py the two ways a call can fail
branding.py the icon clients show, and the routes serving it
assets/ the icon itself, as PNG and SVGThe icon is a hand drawn play button rather than YouTube's official artwork, so there is nothing here that belongs to anyone else.
License
MIT
Available Tools
3 toolsyoutube_playlistA
List the videos in a YouTube playlist, in playlist order.
Returns watch URLs and the playlist title, nothing about the videos themselves. Use it to unpack a playlist, then call youtube_video_facts or youtube_transcript on the URLs you get back. A watch link that happens to be playing inside a playlist works here too.
Inputs: url (required). Returns: count, title, video_urls, playlist_id
youtube_transcriptA
Read what is said in a YouTube video, as plain text.
You get the whole thing by default. On a long video, narrow it with start_seconds and end_seconds so the response stays small. A caption line that straddles either edge of that window comes back whole rather than cut in half.
English is preferred, then a handful of widely spoken languages, and failing all of those whatever the video actually has. Check the language field on the way out and translate if you need to. The auto_generated field tells you whether a human wrote the captions or speech recognition did, which is worth knowing before you quote them.
The text has no timestamps in it. Shorts are not supported. If you only need the title, length or view count, youtube_video_facts is much cheaper.
Inputs: url (required), end_seconds, start_seconds. Returns: text, language, video_id, line_count, +1 more
youtube_video_factsA
Look up a YouTube video without reading its captions.
Gives you the title, channel, duration, publish date, view and like counts, the description, and which caption languages exist. Far cheaper than pulling a transcript, so start here when the question is about the video rather than its contents, or to check a video has captions before asking for them.
Inputs: url (required). Returns: url, likes, title, views, +8 more
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: transcript extracts spoken content, playlist lists videos in a playlist, and video_facts provides metadata. There is no overlap or ambiguity between them.
All tool names follow the same pattern: 'youtube_' prefix followed by a descriptive noun or noun phrase. The naming is consistent and predictable, using lowercase with underscores throughout.
Three tools is a reasonable and well-scoped count for a YouTube-focused MCP server. Each tool covers a core, distinct capability without unnecessary bloat, falling within the typical 3-15 range.
The tool set covers the main YouTube interaction needs: reading transcripts, fetching video metadata, and enumerating playlists. Minor gaps exist (e.g., no search or comment retrieval), but the core workflows are complete and work well together.
Maintenance
Related MCP Connectors
An MCP server that gives any LLM or agent clean YouTube transcripts on demand: a single video, a whole channel, or a playlist, plus AI cleanup of auto-generated captions. API-key auth, credit-based, same backend as the public v1 API. Get a free API key with 25 free credits at youtubetranscriptdownload.com/account.
YouTube transcripts, search, channel browsing, and playlists for AI agents via MCP.
Real-time YouTube transcripts, comments, channels & video search MCP. Local npx or hosted OAuth.
Free YouTube transcripts, no API key: videos, channel lists, latest uploads, bulk download links.
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