Discogs
Connect your Discogs music collection to an LLM client to query, analyze, and get recommendations via natural language.
About
Discogs provides a Cloudflare Workers-based service that allows authenticated users to interact with their personal Discogs music collection using the Model Context Protocol (MCP). It processes natural language queries and returns rich, markdown-formatted responses suitable for AI assistants like ChatGPT or Claude. This server features intelligent mood mapping to translate emotional descriptors into relevant Discogs genres, advanced search intelligence for precise results, and secure OAuth authentication, enabling users to effortlessly search their collection, retrieve release details, analyze statistics, and receive context-aware music recommendations directly from their own library.
Key Features
- Context-Aware Recommendations based on mood, time, and similarity
- Comprehensive Collection Statistics and release details retrieval
- Intelligent Mood Mapping for context-aware music recommendations
- 2 GitHub stars
- Advanced Search Intelligence with OR logic and relevance scoring
- OAuth Authentication for secure Discogs account connection
Use Cases
- Querying your personal Discogs collection for specific artists, genres, or years using natural language.
- Receiving music recommendations from your collection tailored to moods like 'mellow' or contexts like 'rainy day'.
- Analyzing your Discogs collection to view statistics by genre, decade, or format.