lastfm-mcp
Related Servers
Alternatives to lastfm-mcp
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Related Servers
- FlicenseBqualityDmaintenanceEnables interaction with Last.fm music data including searching for artists, albums, and tracks, accessing user listening history, and managing music preferences. Supports both read-only operations and authenticated write operations like scrobbling and loving tracks.345-
- AlicenseBqualityBmaintenanceProvides 41 read-only tools to search and browse Last.fm data, including artists, albums, tracks, user scrobble history, and charts.414 npmMIT
- FlicenseNot gradedqualityCmaintenanceEnables music discovery and recommendations through the free Last.fm API by exposing tools for artist and track search, similarity-based suggestions, genre or mood-based discovery, and personalized recommendations built from a Last.fm user's listening history.-
- AlicenseNot gradedqualityBmaintenanceProvides Last.fm listening analytics and recommendations by combining Last.fm and MusicBrainz metadata, maintaining a local listening index, and recording explicit preferences. Enables queries for listening summaries, taste profiles, artist context, and evidence-backed recommendations via MCP tools.MIT
- AlicenseNot gradedqualityAmaintenanceA Model Context Protocol (MCP) server for Last.fm. Gives AI assistants access to your listening history, music discovery, and detailed track/artist/album information.48MIT
- AlicenseAqualityBmaintenanceLets AI assistants answer questions about your Spotify listening history, including taste evolution, top artists, recently played, and playlist analysis.860 npmMIT
TDQS
Scored across 4 tools
Each tool targets a clearly distinct purpose: top_items returns rankings, recent_scrobbles returns a listening stream, artist_history checks a specific artist, and rediscovery_candidates surfaces overlooked artists. There is little risk of an agent selecting the wrong tool for a given task.
All four tool names follow the same lowercase snake_case noun-phrase pattern. Though not verb_noun, the convention is perfectly consistent and predictable across the set.
Four tools form a compact, purposeful set for a niche Last.fm listening-history server. Each tool earns its place and the scope feels appropriately focused rather than bloated or thin.
The set covers the core Last.fm user-listening workflow: top items, recent activity, specific artist checks, and rediscovery candidates. Minor gaps like user profile info or detailed artist metadata are absent, but agents can still complete meaningful tasks without major dead ends.