Spotify Playlist
A Spotify playlist management server built by Kyle Stratis that enables natural language playlist creation with advanced audio-based similarity matching. Features eight different similarity algorithms (Euclidean, Cosine, Weighted, Energy Match, Mood Match, Rhythm Match, Genre Match, Manhattan) that analyze Spotify's audio features like energy, danceability, valence, and tempo to find similar tracks across catalogs, playlists, artist discographies, or saved libraries. The implementation includes automated playlist creation, customizable feature weighting, and flexible search scopes, making it useful for building workout playlists based on energy levels, mood-based collections using valence matching, or discovering similar tracks within existing playlists using genre analysis.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-19.
Scan details: Circle-IR · 2026-09-19 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- media
- Source
- PulseMCP
- Repository
- github.com/kylestratis/spotify-mcp
- Author type
- human
- Last scanned
- 2026-09-19
- Updated
- 2026-09-19
Use via MCP
Resolve Spotify Playlist from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.