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zebra 32acd038c8 docs: document any-link Odesli resolution in README 
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-13 21:59:59 -07:00

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🎵 MusicFetch

MusicFetch is a smart command-line utility that finds music by searching Lidarr (your music collection manager) and YouTube Music at the same time, shows you the top hits in an interactive picker, and downloads/queues whatever you choose. It accepts:

  • A free-form query: an artist, an album, a track title, or combos like "Artist - Title" or "Artist - Album" (e.g. "ODESZA - Bloom", "Daft Punk", "Discovery").
  • A URL (e.g. "https://music.youtube.com/watch?v=..." or a regular YouTube URL).
  • Any streaming link (Spotify, Apple Music, Tidal, Deezer, …): resolved to metadata via Odesli/song.link, then searched on Lidarr first and downloaded from the matching YouTube track if no Lidarr release is available. YouTube and SoundCloud links download directly.

Lidarr is tried first by default. If you pick a Lidarr album but no indexer release is available, MusicFetch automatically falls through to the top YouTube hit. YouTube downloads prefer YouTube Music URLs so album art and tags are correct.

🚀 Features

  • One unified picker showing the top hits from Lidarr and YouTube together, with matching keywords bolded.
  • Lidarr-first flow: pick an album → adds artist+album (monitored) → interactive indexer search → falls through to YouTube only if no release is found.
  • Accurate YouTube metadata via ytmusicapi (real artist / album / year / album art), with yt-dlp scraping as a fallback.
  • Explicit tag overrides on download so files are tagged from the chosen hit, not from scraped titles.
  • Non-interactive, YouTube-first, dry-run, quality, limit, and source-restriction flags.

📦 Dependencies & Installation

🐍 Python

  • Python 3.10+
  • requests
  • ytmusicapi (recommended — accurate YouTube Music metadata)
  • rich (recommended — nicer picker table + bold keyword matching)
pip install requests ytmusicapi rich

Note: if you hit ModuleNotFoundError: No module named 'idna' from requests, repair it with:

pip install --force-reinstall idna requests

ytmusicapi and rich are optional — without them MusicFetch falls back to yt-dlp search scraping and a plain ANSI picker.

📼 External Tools

  • yt-dlp (audio download/extraction) and ffmpeg (for -x extraction / embedding).
pip install -U yt-dlp
sudo apt install ffmpeg      # or your distro's equivalent

⚙️ Configuration

Set via environment variables:

Variable Default Purpose
LIDARR_API_KEY (required for Lidarr) Lidarr API key.
LIDARR_URL http://localhost:8686 Lidarr base URL.
MUSICFETCH_ROOT /media/music Default output root folder. 
export LIDARR_API_KEY="your-lidarr-api-key"

🧑‍💻 Usage

./musicfetch [OPTIONS] QUERY...

Options

Flag Description
-n, --noninteractive Auto-pick the top hit (no prompt).
-s, --ytsearch Search/select YouTube first instead of Lidarr first.
-d, --dry-run Show every action without executing it.
-q, --quality {best,320,m4a,opus,flac} Audio quality/format (default best).
--limit N Hits per source (default 10).
--lidarr-only Skip YouTube.
--yt-only Skip Lidarr.
-o, --root PATH Output root folder (default /media/music).
--search-all Search all albums when adding an artist to Lidarr.
--repair Re-tag existing downloads under --root from source metadata (see below).
--workers N Parallel metadata fetches during --repair (default 4).
--cookies FILE yt-dlp cookies.txt for authenticated YouTube (avoids bot-check / rate limits).
--cookies-from-browser BROWSER Load YouTube cookies from a local browser (e.g. firefox).
--retag-from-path Offline: re-tag artist/title from folder + filename (see below).
-x, --exclude NAME Folder under --root to skip during --repair/--retag-from-path (repeatable).
--debug Verbose output.

Examples

# Interactive: combined Lidarr + YouTube picker
./musicfetch "ODESZA - Bloom"

# Just an artist / just an album / just a title all work
./musicfetch "Daft Punk"
./musicfetch "Discovery"

# YouTube first, auto-pick top hit
./musicfetch -s -n "Daft Punk - Harder Better Faster Stronger"

# Dry run — see what would happen, change nothing
./musicfetch -d "ODESZA - Bloom"

# YouTube only, lossless preferred
./musicfetch --yt-only -q flac "Bonobo - Kerala"

# Download by URL (single track or playlist/set/album, any yt-dlp site)
./musicfetch "https://music.youtube.com/watch?v=xxxxxxxxxxx"
./musicfetch "https://soundcloud.com/artist/sets/my-mix"

🔧 Repair existing tags

--repair walks <root>/<artist>/<source>/ (the youtube/soundcloud/… download folders — Lidarr album folders are skipped), re-fetches authoritative metadata for each file using the [id] in its filename, and fixes tags. Useful when downloads landed with missing album or wrong year.

It is deliberately conservative: it overwrites album and year (the usual breakage), and fills in artist/title when they are missing or a known-bogus placeholder (NA, Unknown Album, Unknown Artist — left behind by older buggy tagging) — but it never overwrites a genuine existing artist/title with a channel name or decorated video title. A bogus NA [<id>].<ext> filename is renamed to the recovered title, and a literal NA album with no source album is normalised to Unknown Album.

Each file is its own yt-dlp network round-trip, so repair runs them in a thread pool; --workers N (default 4) caps concurrency. Progress prints every 100 files. Requires mutagen (a yt-dlp dependency, usually already present). CLI-only — not exposed via the REST API.

Cookies (important for bulk repair). Unauthenticated YouTube requests get throttled fast — a large --repair (or even a --dry-run, which still fetches) will trip "Sign in to confirm you're not a bot" (HTTP 429) and every subsequent call fails until the IP-level flag clears. Pass authenticated cookies to avoid it:

./musicfetch --repair --cookies /path/cookies.txt -o /media/music        # exported cookies.txt
./musicfetch --repair --cookies-from-browser firefox -o /media/music     # or read from a browser

With cookies you can raise --workers; without them keep it low (≤4) and expect occasional throttling. Cookies also apply to normal fetches/downloads. The same can be set for the API container via $YTDLP_COOKIES / $YTDLP_COOKIES_FROM_BROWSER. If you do get flagged, stop — retrying extends it; wait ~30-60 min (429) or longer for a bot-check.

Getting YouTube cookies

⚠️ Use a throwaway / secondary Google account, not your main one — bulk automated requests can get the account flagged. You must be logged in to YouTube in the browser first.

Option A — read straight from the browser (simplest, host CLI only). --cookies-from-browser reads the browser's own cookie store, so there's nothing to export:

./musicfetch --repair --cookies-from-browser firefox -o /media/music
./musicfetch --repair --cookies-from-browser chrome  -o /media/music
  • Firefox: works while open; just be logged in to YouTube.
  • Chrome / Chromium / Brave / Edge: must be fully quit when you run this (Chrome locks its cookie DB, and newer versions encrypt it — close the browser entirely first). On Linux a running Chrome will usually fail with a "could not copy cookie database / locked" error.
  • Specify a profile if not the default, e.g. --cookies-from-browser "chrome:Profile 1".

This only works where the browser lives (your host), not inside the Docker container.

Option B — export a cookies.txt (works anywhere, incl. the container/server). Use a Netscape-format cookie exporter, then point --cookies / $YTDLP_COOKIES at the file:

  1. Install a cookies exporter extension:

    • Firefox: "cookies.txt" (a.k.a. Export Cookies).
    • Chrome: "Get cookies.txt LOCALLY" (pick a LOCALLY-running one — avoid extensions that upload your cookies anywhere).

  2. Log in to https://www.youtube.com, click the extension, Export → save cookies.txt.

  3. Use it:

    ./musicfetch --repair --cookies ~/cookies.txt -o /media/music

    For the API container, mount it and set the env var (see server/docker-compose.yml):

    environment:
  YTDLP_COOKIES: "/cookies.txt"
volumes:
  - /host/path/cookies.txt:/cookies.txt:ro

Cookies expire — if YouTube starts rejecting them, re-export. Treat cookies.txt like a password (it is your logged-in session); keep it out of git (.gitignore it).

# Preview what would change (writes nothing)
./musicfetch --repair -d

# Apply fixes under a specific root
./musicfetch --repair -o /media/music

--retag-from-path is an offline companion: it derives artist and title purely from the folder name + filename (stripping (Official Video) / (Lyrics)-style decorations, and treating an Artist - Title filename correctly), with no network. Use it to undo bad tags — e.g. titles/artists clobbered by an earlier --repair on music videos. It overwrites artist/title and leaves album/year alone.

./musicfetch --retag-from-path -d            # preview
./musicfetch --retag-from-path -o /media/music

# Skip folders (e.g. hand-curated playlists you don't want re-tagged)
./musicfetch --repair -x Unsorted -x playlists

📁 Output Structure

<root>/
├── Artist Name/
│   ├── Album Name/    (managed by Lidarr)
│   ├── youtube/       (YouTube / YouTube Music downloads)
│   ├── soundcloud/    (SoundCloud downloads)
│   └── <source>/      (one folder per yt-dlp source)

❓ Troubleshooting

  • No Lidarr hits / "LIDARR_API_KEY not set": export your key and confirm LIDARR_URL is reachable.
  • Wrong album art from YouTube: install ytmusicapi so MusicFetch can resolve proper YouTube Music URLs and metadata.
  • yt-dlp errors: update with yt-dlp -U; ensure ffmpeg is installed for extraction/embedding.
  • idna import error: pip install --force-reinstall idna requests.
  • Permission denied writing files: ensure the output root exists and is writable (-o/--root or MUSICFETCH_ROOT).

🌐 REST API (Docker)

Run MusicFetch as an authenticated HTTP service inside your Lidarr Docker stack. A client POSTs a query; the server grabs the top hit non-interactively and runs the download as a background job you can poll. Every response includes a human-readable message (handy for Siri).

Configure & run

Set the network name in server/docker-compose.yml to your existing Lidarr stack network, then:

export LIDARR_API_KEY="your-lidarr-key"
export MUSICFETCH_API_KEY="a-long-random-secret"
docker compose -f server/docker-compose.yml up -d --build
Env var Default Purpose
MUSICFETCH_API_KEY (required) Shared secret clients send as X-API-Key.
MUSICFETCH_PORT 6769 Listen port.
LIDARR_URL http://lidarr:8686 Lidarr base URL (stack network).
LIDARR_API_KEY (required for Lidarr) Lidarr API key.
MUSICFETCH_ROOT /media/music Music output root (bind-mounted).

TLS is expected to be handled by your upstream reverse proxy; the container serves plain HTTP on 6769.

Endpoints

Method Path Auth Purpose
GET /health no Liveness check.
POST /fetch?q=... yes Grab top hit; returns a job_id.
GET /jobs/{id} yes Poll job status.

POST /fetch params: q (required), quality (best,320,m4a,opus,flac), source (auto,lidarr,youtube).

curl examples

# Kick off a fetch
curl -X POST 'https://mf.izebra.net/fetch?q=Under%20My%20Skin' \
  -H 'X-API-Key: a-long-random-secret'
# -> {"message":"Found 'Under My Skin' ... Downloading now.","job_id":"a1b2c3","status":"queued","hit":{...}}

# Poll the job
curl 'https://mf.izebra.net/jobs/a1b2c3' -H 'X-API-Key: a-long-random-secret'
# -> {"message":"Finished downloading ...","status":"done","result":{...}}

🗣️ Siri Shortcuts integration

Make a shortcut that fetches music by voice ("Hey Siri, fetch music").

  1. Shortcuts app → New Shortcut.
  2. Add Ask for Input → Input Type Text, prompt "What should I fetch?". (Or use Dictate Text for fully spoken input.)
  3. Add Text action, set it to: https://mf.izebra.net/fetch?q= then insert the Provided Input variable at the end. (Shortcuts URL-encodes query variables automatically.)
  4. Add Get Contents of URL:
    • URL: the Text variable from step 3.
    • Method: POST.
    • Headers: add one — key X-API-Key, value your MUSICFETCH_API_KEY.
    • Request Body: leave as is (the query is in the URL).
  5. Add Get Dictionary Value → Get Value for message in Contents of URL.
  6. Add Speak Text → the Dictionary Value. Siri reads back "Found '…' … Downloading now."
  7. (Optional) To confirm completion: add Get Dictionary Value for job_id, Wait ~20 seconds, Get Contents of URL on https://mf.izebra.net/jobs/<job_id> (same X-API-Key header), then Get Dictionary Value message → Speak Text again.

Rename the shortcut (e.g. "Fetch Music") — that phrase becomes the Siri trigger.

🛠️ Contributing

PRs welcome. This script is middleware around Lidarr + yt-dlp, not a Lidarr replacement. Keep it a single bash-friendly executable.

📜 License

GPL V3.0

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