vdl-mcp
Click on "Install 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., "@vdl-mcpdownload this YouTube video and summarize the transcript"
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.
vdl-mcp connects an AI assistant to your own vdl server over the Model Context Protocol. The real power is the Whisper synergy:
Download → transcript → the assistant understands the content.
So you can say things like:
"Download this YouTube video and summarize it."
"Grab that cooking clip and write out the recipe as a list."
"What was said about X in this interview?"
"Download the audio of this talk and give me the key points."
How it works
It's a small stdio MCP server that talks to vdl's REST API and authenticates with your existing API token. Nothing runs inside vdl itself.
Tool groups are toggleable with safe defaults:
Group | Tools | Default |
Read |
| ✅ on |
Download |
| ✅ on |
Transcribe |
| ✅ on |
Delete |
| ❌ off |
Bulk |
| ❌ off |
Settings |
| ❌ off |
A disabled group is invisible to the assistant.
Related MCP server: popcorn
Requirements
A running vdl instance.
An MCP token: in vdl open the MCP tab → create token and copy it. This token is scoped — it may only perform the MCP actions you enable there (write/delete tools respect the toggles and read-only mode, everything else is refused server-side), so it's safer than the general API token.
Install
With pipx (puts vdl-mcp on your PATH):
pipx install git+https://github.com/sphings79/vdl-mcpor with uv:
uv tool install git+https://github.com/sphings79/vdl-mcpConnect it to Claude Desktop
Add this to your Claude Desktop config (claude_desktop_config.json):
{
"mcpServers": {
"vdl": {
"command": "vdl-mcp",
"env": {
"VDL_URL": "http://localhost:8000",
"VDL_TOKEN": "your-api-token"
}
}
}
}Restart Claude Desktop — the vdl tools appear. (Any MCP-capable client works the same way; just run the vdl-mcp command over stdio.)
Run with Docker
Prefer a container? A prebuilt image is published to GHCR — use it as the command:
{
"mcpServers": {
"vdl": {
"command": "docker",
"args": ["run", "-i", "--rm",
"-e", "VDL_URL", "-e", "VDL_TOKEN",
"ghcr.io/sphings79/vdl-mcp:latest"],
"env": {
"VDL_URL": "http://host.docker.internal:8000",
"VDL_TOKEN": "your-api-token"
}
}
}
}Note the -i (keep stdin open for stdio) and, when vdl runs on the same host, host.docker.internal so the container can reach it.
No web UI — by design
vdl-mcp is a stdio process launched locally by your MCP client. It does not open a network port, so it has no login page and no fail2ban — there is nothing inbound to protect. Its security model is: keep your API token private, leave destructive tools off (the defaults), and optionally set a domain allowlist. Authentication and brute-force protection live in vdl itself. (If you ever want a remote, multi-client HTTP server instead, that's a different transport — open an issue.)
Tools
resolve(url)— analyze a link, list items and available qualities (no download).download(url, audio=False, section="", wait=True)— download best quality (or MP3);sectionlike0:30-1:00clips;waitreturns the finished filename.transcribe(name, language="")— Whisper transcription → returns the text (requires a Whisper model set in vdl).get_transcript(name)— return an existing transcript's text.list_files(query, service, label, limit)— browse your downloads.job_status(job_id)— check a download job.(off by default)
delete_file,bulk,get_settings.
Configuration (environment variables)
Variable | Default | Meaning |
|
| Base URL of your vdl instance |
| (empty) | vdl MCP token (from the MCP tab) |
|
| Kill switch: expose only read tools (no download/transcribe/delete/bulk) |
|
| resolve/list/status/get_transcript |
|
| download |
|
| transcribe |
|
| delete files |
|
| bulk actions |
|
| read settings |
| (unset) | Per-tool override, e.g. |
| (empty = any) | comma-separated host suffixes the assistant may download from |
|
| default request timeout (seconds) |
Every tool is tagged in its description — [read], [writes] or [deletes] — so both you and the assistant can see its risk at a glance.
Manage it from vdl's web UI too: in vdl go to Settings → MCP tab to toggle each tool (with a read-only master switch and risk chips). vdl-mcp fetches that config at startup, so no env vars are needed — restart vdl-mcp after changes. Precedence for whether a tool is exposed: read-only (env or UI) → per-tool env override → web UI → group flag.
Security notes
The assistant acts as you via your token — keep it private.
Destructive tools are off by default. Enable them consciously.
Downloading an arbitrary URL on an assistant's request has a prompt-injection surface. Set
VDL_MCP_DOMAIN_ALLOWLIST(e.g.youtube.com,instagram.com) to restrict it.Only for content you own or have the rights/permission to download — the same disclaimer as vdl applies.
License
GNU Affero General Public License v3.0 (AGPL-3.0) — see LICENSE. © 2026 sphings79
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