by cswkim
Access the Discogs website to search music databases, manage your collection, and browse marketplace listings with detai
Connects to the Discogs music database API to search for artists and releases, browse marketplace listings, and manage music collections.
Discogs is a community-built MCP server published by cswkim that provides AI assistants with tools and capabilities via the Model Context Protocol. Access the Discogs website to search music databases, manage your collection, and browse marketplace listings with detai It is categorized under other.
You can install Discogs in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
Discogs is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
README content is unavailable from source data for this server.
Open GitHub repository →Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
Discogs reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
We evaluated Discogs against two servers with overlapping tools; this profile had the clearer scope statement.
Useful MCP listing: Discogs is the kind of server we cite when onboarding engineers to host + tool permissions.
I recommend Discogs for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Discogs reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Discogs is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
According to our notes, Discogs benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Discogs has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Discogs is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
I recommend Discogs for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
showing 1-10 of 71
YggTorrent
Securely access YggTorrent with an unofficial API for torrent search, category filtering, metadata, and magnet link gene
★ 79.9K
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
