1001 Albums Generator MCP

AI-powered exploration of your 1001 Albums listening journey

Install · Tools · Prompts · Contributing

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What is this?

1001 Albums Generator — built by u/SidledsGunnar — is a web app that assigns you one album at a time from the canonical 1001 Albums You Must Hear Before You Die list, and asks you to listen and rate it. It's a brilliant way to systematically explore music history, and it quietly accumulates a rich personal dataset as you go: your ratings, your written reviews, your listening timeline.

1001 Albums Generator MCP connects that dataset to AI assistants via the Model Context Protocol, so you can explore it through natural conversation instead of manually browsing the site.

You:    What's today's album?
Claude: Today's album is Miles Davis — Kind of Blue (1959).
        One of the most influential jazz recordings ever made, featuring
        Coltrane, Cannonball Adderley, and Bill Evans. Community rating: ★ 4.63

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Capabilities

Area	What the AI can do
🎵 Daily listening	Retrieve today's album with background, context, and personal pitch
📚 History	Browse, search, and explore your full listening archive
📊 Taste analysis	Genre affinities, decade distributions, rating tendencies, community alignment
🧠 Pattern recognition	Arc analysis, milestone detection, listening journey narrative
🔍 Review insights	Synthesise your written reviews to understand your own taste
👥 Groups	Compare members, find divisive albums, map taste compatibility

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Installation

Note: This server enforces a 20-second minimum interval between upstream API calls and caches responses for 4 hours to stay within the upstream rate limit of 3 requests/minute. First requests after a cache miss may be slow — this is a constraint of the 1001 Albums Generator API, not the server.

Option A — Claude MCP Bundle (recommended)

No Node.js required for the remote version.

1. Go to the releases page and download a .mcpb file:

   File	What it does
   *-remote.mcpb	Connects to the hosted server — zero local setup
   *-local.mcpb	Runs the MCP server locally on your machine

2. Open Claude Desktop → Settings → Extensions

3. Drag and drop the .mcpb file into the window

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Option B — Remote HTTP Server (no install)

Point any MCP client at the hosted server:

https://1001-albums-mcp.bnm12.dk/mcp

Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "1001-albums": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://1001-albums-mcp.bnm12.dk/mcp"]
    }
  }
}

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Option C — Local Installation

Requirements: Node.js 18+

git clone https://github.com/bnm12/1001-albums-generator-mcp.git
cd 1001-albums-generator-mcp
npm install && npm run build

Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "1001-albums": {
      "command": "node",
      "args": ["/absolute/path/to/dist/index.js"],
      "env": { "MCP_MODE": "stdio" }
    }
  }
}

As an HTTP server (for any MCP client over HTTP):

MCP_MODE=http PORT=3000 node dist/index.js
# Endpoint: http://localhost:3000/mcp

Restart Claude Desktop after any config change.

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MCP Tools Reference

Project tools

Tool	Description
get_album_of_the_day	Today's assigned album with full metadata and project notes
get_project_stats	Progress summary: generated, rated, unrated, current album
list_project_history¹	Full history with sort and pagination
search_project_history	Search history by artist, album, year, genre, or character — multi-word queries use OR matching
get_album_detail²	Full detail for one album: review, streaming links, subgenres
get_album_context	Artist arc, musical connections, community divergence, listening journey

Meta tools

Tool	Description
get_tool_guide	Returns the full workflow guide — recommended tool sequences, signal weighting, common mistakes

Analysis tools

Tool	Description
get_taste_profile	Genres, decades, rating tendencies, community alignment
get_rating_outliers	Albums where your ratings diverge most from the community
get_review_insights³	Synthesise your written reviews into qualitative taste insight
get_listening_arc	Segmented journey analysis with trends and milestones

Group tools

Tool	Description
get_group	Summary: members, current album, all-time high/low
get_group_latest_album	Latest group album with all member votes
get_group_album_reviews	Every member's rating and review for a specific album
get_group_album_insights	Most divisive and most consensus albums by rating variance
get_group_member_comparison	Side-by-side taste comparison between two members
get_group_compatibility_matrix	Group-wide pairwise compatibility — who agrees with whom
compare_projects	High-level comparison of any two projects

Community tools

Tool	Description
list_book_album_stats	Community ratings for all ~1001 canonical book albums
get_book_album_stat	Search book albums by name, artist, genre, or year
list_user_submitted_album_stats	Stats for user-submitted albums outside the book list
refresh_data	Force-refresh cached data for any dataset

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¹ List and search tools return a slim format — no reviews, streaming links, or images. Use get_album_detail when you need a written review, a Spotify/Apple Music link, or full genre breakdown.

² Identify albums by name, UUID, or generatedAlbumId (available from list/search results).

³ get_review_insights attempts to use MCP Sampling to synthesise reviews. Most clients including Claude Desktop do not currently support sampling — the tool automatically falls back to returning the raw reviews with synthesis instructions for the agent to complete directly. Output quality is equivalent either way.

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Prompt Templates

Compatible clients (e.g. Claude Desktop) surface these as one-click conversation starters.

Prompt	Description
todays-album	Background and context on today's assigned album
predict-my-rating	Predict how you'll rate today's album based on your history
taste-profile	Full taste analysis and listener archetype
album-deep-dive	Deep contextual analysis of a specific album in your history
rating-outliers	Where your taste diverges most from the community
genre-journey	How your genre exposure has evolved over time
listening-wrapped	Spotify Wrapped-style summary of your listening history
personalized-pitch	Persuasive, taste-grounded case for a specific album
group-latest-album	How your group rated their latest album
group-compatibility	Who in your group has the most similar and different taste
group-divisive-albums	Albums that split your group — and ones you all agreed on
compare-members	Detailed taste comparison between two group members

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Example Prompts

Daily

What's today's album from my project?
Give me a personalised pitch for why I should care about today's album.
Predict how I'll rate today's album and explain your reasoning.

History & taste

Build a full profile of my music taste.
Which decade dominates my listening history?
Which albums did I rate way above the community average?
How has my taste evolved over time?

Discovery

Give me a deep dive on Kind of Blue from my history.
Find connections between the last five albums I listened to.
What does my review history say about what I actually value in music?

Group

What did everyone in our group think of the latest album?
Who in our group has the most similar taste to me?
Which album has divided our group the most?

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Contributing

Contributions are welcome. Some ideas:

• New analysis tools (recommendation engine, mood inference, BPM/key data)
• Deeper genre clustering
• Visual listening stats

Before opening a PR, run the full check suite:

npx tsc --noEmit   # strict TypeScript
npm run lint       # ESLint
npm run build
npm test

When adding tools, register them in createMcpServer() in src/index.ts and update README.md, AGENTS.md, and src/content/resources/tool-guide.md. The updated tool-guide is automatically returned by get_tool_guide — no additional step needed. See AGENTS.md for the full contribution guide.

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License

ISC © 2026 bnm12

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Built for music nerds doing the 1001 Albums challenge
Thanks to u/SidledsGunnar for building the generator that makes all of this possible
Powered by Model Context Protocol