Discogs MCP Server
Provides tools for searching Discogs catalog and user collections, finding best pressings of albums, getting mood- and taste-based recommendations, exploring other users' collections, and managing wantlists.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Discogs MCP Serverfind the best pressing of Kind of Blue"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Discogs MCP Server
A remote Model Context Protocol server for Discogs, hosted on Cloudflare Workers. Two things it's good at:
Finding the best-sounding pressing of an album — surveys every version of a master release, scores each on community ratings, collector demand, format quality, and audiophile markers (MFSL, half-speed masters, renowned mastering engineers, Japanese pressings…), and returns a ranked comparison.
Mood- and taste-based recommendations — mood-aware search of your own collection ("mellow Sunday morning"), catalog discovery ranked against your taste profile, and cross-user discovery that mines other collectors' public collections.
Auth is browser-based Discogs OAuth: connect an MCP client to the server URL and you'll be redirected to Discogs to log in. Read-only — the server never modifies your collection.
Quick start (self-hosting)
Prerequisites: Node 18+, a Cloudflare account, and a Discogs developer app.
npm install
npm run setup:kv # creates OAUTH_KV and CACHE_KV; paste the IDs into wrangler.toml
cp .dev.vars.example .dev.vars # fill in your Discogs consumer key/secret
npm run dev # local dev on http://localhost:8787Register the Discogs app with callback URL http://localhost:8787/callback for dev. Test with the MCP Inspector:
npm run inspectDeploy
wrangler secret put DISCOGS_CONSUMER_KEY
wrangler secret put DISCOGS_CONSUMER_SECRET
npm run deployThen update your Discogs app's callback URL to https://<your-worker>.workers.dev/callback.
Connect a client
Claude Code:
claude mcp add --transport http discogs https://<your-worker>.workers.dev/mcpClaude Desktop / claude.ai: add a custom connector with URL
https://<your-worker>.workers.dev/mcpLegacy SSE clients can use
/sseinstead of/mcp.
To restrict who can log in, set ALLOWED_DISCOGS_USERS in wrangler.toml (comma-separated Discogs usernames and/or numeric user IDs).
Related MCP server: Navidrome-MCP
Tools
Tool | What it does |
| Health, identity, capabilities |
| Mood-aware search of your collection ( |
| Full catalog search; results marked |
| Release / master details with community data |
| All pressings of a master, filterable by country/format |
| Score & rank pressings of an album (by |
| Side-by-side comparison of 2–5 release IDs |
| Genre/style/decade/format/label analytics + taste profile |
| Browse another user's public collection |
| Your wantlist, or another user's |
| Recommendations by mood, genre/style, or reference release |
| Profile-based discovery; cross-user mining with |
Prompts: find-best-pressing, recommend-by-mood, cross-user-discovery, compare-pressings.
Resources: discogs://collection, discogs://wantlist, discogs://release/{id}, discogs://master/{id}, discogs://master/{id}/versions, discogs://user/{username}/collection, discogs://user/{username}/wants.
Example conversations
"What's the best pressing of OK Computer?" →
find_best_pressingranks the top versions with score breakdowns and audiophile signals.
"What should I listen to on a rainy evening — something I already own?" →
search_collectionmaps "rainy" to Cool Jazz / Ambient / Shoegaze / Post-Rock / Trip Hop and filters your collection.
"Compare my collection with user xyz and tell me what to buy next." →
discover_similarreports your profile similarity and their albums that best match your taste.
Architecture notes
Auth bridge: MCP clients speak OAuth 2.1 to the Worker (via
@cloudflare/workers-oauth-provider); the Worker speaks OAuth 1.0a to Discogs. Discogs tokens live encrypted inside the MCP access token (props) — no server-side session store.Caching: all Discogs reads go through a KV read-through cache (releases/masters 24 h, versions 12 h, search 6 h, collections/wantlists 4 h). Collections are additionally cached as a single slim aggregate, so mood search, stats, and recommendations cost zero API calls when warm.
Rate limits: Discogs allows 60 req/min authenticated. The client retries 429s with exponential backoff and soft-throttles when the remaining budget is low.
find_best_pressingbudgets calls by pre-ranking versions on collector signals and fetching details only for the top ~12 candidates (the versions endpoint carries no ratings).Collections are fetched at 100 items/page up to 3,000 items; beyond that results are truncated and flagged (
truncated: true).
Development
npm test # vitest unit tests (scoring, mood mapping, similarity)
npm run lint # tsc --noEmit
npm run build # wrangler dry-run bundleLicense
MIT
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