Spotify Playlist Curator MCP Server
LocalAbout Spotify Playlist Curator MCP Server
An MCP server for Spotify users that analyzes playlist audio characteristics and uses Claude to suggest tracks. It also supports Spotify search and playlist editing.
Key features
- 01Analyze playlist audio features
- 02Summarize mood, energy, and tempo
- 03Get Claude-based song recommendations
- 04Search Spotify tracks
- 05Add tracks and create playlists
Use cases
- 01Understand a playlist’s mood and tempo
- 02Find songs matching an existing playlist
- 03Add recommended tracks to a playlist
- 04Create a new Spotify playlist
MCP support
Exposes playlist listing and analysis, Claude recommendations, track search, and playlist creation or editing as tools for MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMESpotify Playlist Curator MCP Server
An MCP server that helps curate Spotify playlists by analyzing your existing tracks and using Claude AI to recommend songs based on mood, vibe, BPM, and other musical attributes.
Features
- Connect to your Spotify account and access your playlists
- Analyze the audio features of tracks in your playlists
- Generate a summary of playlist mood, energy, tempo, and other characteristics
- Get song recommendations from Claude AI based on the playlist analysis
- Search for tracks on Spotify
- Add recommended tracks to your playlists
- Create new playlists
Setup
Prerequisites
- Node.js (v14 or higher)
- A Spotify Developer account and registered application
- Claude access via MCP (Machine Conversation Protocol)
Installation
-
Clone this repository:
git clone https://github.com/lechiffre1/Spotify-Playlist-Curator-MCP-Server.git cd Spotify-Playlist-Curator-MCP-Server -
Install dependencies:
npm install -
Create a
.envfile based on the provided.env.example:cp .env.example .env -
Set up your Spotify Developer credentials:
- Go to Spotify Developer Dashboard
- Create a new application
- Add
http://localhost:3000/callbackas a Redirect URI - Copy your Client ID and Client Secret to the
.envfile
-
Start the server:
npm start
Usage
Authentication
When you start the server, you'll need to authenticate with Spotify first:
- Visit
http://localhost:3000/loginin your browser - Log in with your Spotify account and authorize the application
- After successful authentication, you can close the browser window and return to your MCP client
MCP Methods
The following MCP methods are available:
getPlaylists
Returns a list of your Spotify playlists.
const response = await client.getPlaylists();
getPlaylistDetails
Gets detailed information about a specific playlist, including track analysis.
const response = await client.getPlaylistDetails({
playlistId: "your_playlist_id"
});
getClaudeRecommendations
Gets song recommendations from Claude AI based on playlist analysis.
const response = await client.getClaudeRecommendations({
playlistId: "your_playlist_id",
count: 10 // Optional, defaults to 10
});
addRecommendationsToPlaylist
Adds recommended tracks to a playlist.
const response = await client.addRecommendationsToPlaylist({
playlistId: "your_playlist_id",
trackUris: ["spotify:track:id1", "spotify:track:id2", ...]
});
searchTracks
Searches for tracks on Spotify.
const response = await client.searchTracks({
query: "search query",
limit: 10 // Optional, defaults to 10
});
createPlaylist
Creates a new Spotify playlist.
const response = await client.createPlaylist({
name: "My New Playlist",
description: "Created by Spotify Playlist Curator", // Optional
isPublic: false // Optional, defaults to false
});
Example Client Usage
import { createClient } from '@anthropic-ai/mcp-client';
async function main() {
// Create MCP client
const client = createClient({
serverUrl: 'http://localhost:3000',
anthropicApiKey: 'your_anthropic_api_key' // Required for Claude integration
});
// 1. Get user playlists
const playlists = await client.getPlaylists();
console.log('Your playlists:', playlists);
// 2. Select a playlist and get its details
const playlistId = playlists.playlists[0].id;
const playlistDetails = await client.getPlaylistDetails({ playlistId });
console.log('Playlist summary:', playlistDetails.summary);
// 3. Get recommendations from Claude
const recommendations = await client.getClaudeRecommendations({ playlistId });
console.log('Claude recommendations:', recommendations.claudeRecommendations);
// 4. Add recommendations to the playlist
const trackUris = recommendations.claudeRecommendations
.filter(track => track.matched)
.map(track => track.uri);
if (trackUris.length > 0) {
const result = await client.addRecommendationsToPlaylist({ playlistId, trackUris });
console.log('Added recommendations:', result);
}
}
main().catch(console.error);
License
MIT
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.