AI Analysis
The package is assessed as safe with a low risk score due to the absence of obfuscation and credential harvesting patterns, along with no immediate signs of malicious intent.
- No obfuscation detected
- No credential harvesting patterns
Per-check LLM notes
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer has only one package, which may indicate a new or less active account, but there are no other red flags.
Package Quality Overall: Medium (6.6/10)
Test suite present — 9 test file(s) found
Test runner config found: conftest.pyTest runner config found: pyproject.toml9 test file(s) detected (e.g. integration_test.py)
Some documentation present
Detailed PyPI description (19805 chars)
No contributing guide or governance files found
Development Status classifier >= Beta
Partial type annotation coverage
106 type-annotated function signatures detected in source
Active multi-contributor project
5 unique contributor(s) across 100 commits in epheterson/applemusic-mcpActive community — 5 or more distinct contributors
Heuristic Checks
Found 1 network call pattern(s)
} response = requests.get( "https://api.music.apple.com/v1/me/library/play
No obfuscation patterns detected
Found 6 shell execution pattern(s)
- Scripts are executed via subprocess.run() with capture_output=True and a 30-second timeout to""" try: result = subprocess.run( ["osascript", "-e", script], capture_output=Truin Music app try: subprocess.run(["open", music_url], check=True, capture_output=True)cts to Music try: subprocess.run(["open", https_url], check=True, capture_output=True)f"). """ try: subprocess.run(["open", "-a", "Music"], check=False, timeout=5) excepttry: r = subprocess.run( [ "osascript",
No credential harvesting patterns detected
No typosquatting candidates detected
No author email provided
All external links appear legitimate
Repository epheterson/applemusic-mcp appears legitimate
1 maintainer concern(s) found
Author "Eric Pheterson" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a Python-based mini-application named 'AppleTuneMaster' that leverages the 'applemusic-mcp' package to manage playlists and control playback on macOS systems. This application should allow users to perform various actions such as adding songs to playlists, removing songs from playlists, pausing/resuming playback, skipping to the next song, and retrieving details about their music library. The application should have a simple command-line interface (CLI) for ease of use. Here are the core functionalities: 1. List all available playlists. 2. Create new playlists. 3. Add songs to existing playlists. 4. Remove songs from playlists. 5. Pause/Resume playback. 6. Skip to the next song. 7. Retrieve information about the current track playing. 8. Display the user's entire music library with basic details (artist, album, track name). Additionally, consider implementing these advanced features: - Search functionality within the music library. - Sort playlists by creation date or alphabetical order. - Provide statistics about the music library (e.g., number of tracks, total duration). - Allow users to set their favorite playlists as default for quick access. For each feature, ensure you're using the 'applemusic-mcp' package effectively to interact with Apple Music's API and control the playback on macOS. The application should handle errors gracefully and provide meaningful feedback to the user.
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