minkdb 0.1.0

A metadata-link between iTunes and MusicBrainz

Mink-db

A metadata-link between iTunes and MusicBrainz. A CLI tool that catalogs a music library by scanning iTunes libraries and retrieving MusicBrainz Release Group IDs.

How-it-works

1. Locates your iTunes Library: Scans a directory for the iTunes Music Library.xml file.
2. Parses Tracks: Reads and indexes individual track metadata from the XML library.
3. Aggregates Albums: Groups tracks into unique album entities based on tags.
4. References the Catalog: Compares found albums against the local ./minkdb database of existing matches.
5. Reconciles (MusicBrainz): Queries the MusicBrainz API to link local albums to official IDs.
6. Generates Output: Finalizes the metadata-link and updates the local data store.

Installation

Mink-db requires Python 3.13 or later.

# Run directly with uvx (no installation required)
uvx minkdb --help

# Or install as a tool
git clone https://github.com/thomaseleff/minkdb.git
cd minkdb
uv tool install .

Quick Start

Catalog your iTunes library and get MusicBrainz IDs:

minkdb --path "M:\Music\iTunes"

Usage

# Basic usage (defaults to current directory)
minkdb

# Specify iTunes library path
minkdb --path "M:\Music\iTunes"

# Limit number of albums processed
minkdb --path "M:\Music\iTunes" --limit 10

# Save output to file
minkdb --path "M:\Music\iTunes" -o ids.json

# Retry matching for previously unmatched albums
minkdb --path "M:\Music\iTunes" --rematch

Output Format

Mink-db outputs a JSON array of matched MusicBrainz IDs:

[
  {"MusicBrainzId": "41656317-c512-456f-9fe7-1f7fb8482a34"},
  {"MusicBrainzId": "8ccd44fb-1c4a-4c5f-98b5-cf3b35a2aa5c"}
]

How It Works

1. Reads iTunes XML: Parses iTunes Music Library.xml for album metadata
2. Deduplicates: Groups tracks by (artist, album) to avoid duplicate queries
3. Queries MusicBrainz: Searches for Release Group IDs using exact artist + album matching
4. Caches Results: Stores results in .minkdb/catalog.json (append-only)
5. Outputs: Prints matched IDs to stdout or file

On subsequent runs, Mink-db will skip already-matched albums and only query MusicBrainz for new ones.

Data Storage

• Catalog database: <library_path>/.minkdb/catalog.json
• Append-only: Previous entries are preserved and updated

Requirements

• Python 3.13+
• iTunes Music Library.xml file
• Internet connection (for MusicBrainz queries)