io.github.khglynn/spotify-bulk-actions-mcp

io.github.khglynn/spotify-bulk-actions-mcp

An MCP server for bulk Spotify operations enabling batch playlist creation, library exports, and large-scale library management with confidence scoring and human-in-the-loop for uncertain matches.

Category
Visit Server

README

<p align="center"> <img src="logo.png" alt="Spotify Bulk Actions MCP" width="200"> </p>

Spotify Bulk Actions MCP

<!-- mcp-name: io.github.khglynn/spotify-bulk-actions-mcp -->

A Model Context Protocol (MCP) server for bulk Spotify operations - batch playlist creation, library exports, and large-scale library management.

What makes this different from other Spotify MCPs?

  • Confidence scoring - Batch searches return HIGH/MEDIUM/LOW confidence for each match
  • Human-in-the-loop - Uncertain matches are exported for review, then re-imported
  • Bulk operations - Handle 500+ songs efficiently with rate limiting built-in
  • Library exports - Export your complete library data
  • Podcast playlist focused - Built specifically for importing song lists from podcast show notes

Support This Project

Made cause I can't not have headphones on, support my 80k+ pocast subscriptions. Buy Me A Coffee


Listed On

Directory Link
PyPI pypi.org/project/spotify-bulk-actions-mcp
mcp.so mcp.so/server/spotify-bulk-actions-mcp
awesome-mcp-servers PR #1541 (pending)

Projects I've Built With This

Project Description Links
recordOS Which albums do you love most? A visual album collection app Live · Repo
Festival Navigator Navigate multi-day festivals with friends Repo

Playlists Maintained With This MCP

Coming soon: Switched On Pop, This American Life, and more podcast playlists


What This Does

Library Analysis:

  • Get all your followed artists
  • Get all saved/liked songs (handles libraries up to 10k songs)
  • Find unique artists from your library ranked by song count
  • Find albums where you have 6+ saved songs (great for vinyl shopping!)
  • Export your complete library summary

Bulk Playlist Creation:

  • Import song lists from CSV files (for podcast playlists, etc.)
  • Batch search with confidence scoring (HIGH/MEDIUM/LOW)
  • Automatic handling of uncertain matches for human review
  • Create playlists from search results

Quick Start

1. Prerequisites

  • Python 3.10+
  • A Spotify account
  • Spotify Developer credentials (get them here)

2. Clone & Setup

# Clone the repo
git clone https://github.com/khglynn/spotify-bulk-actions-mcp.git
cd spotify-bulk-actions-mcp

# Create and activate virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install the package
pip install -e .

# Copy env example and add your credentials
cp .env.example .env
# Edit .env with your SPOTIFY_CLIENT_ID and SPOTIFY_CLIENT_SECRET

Also on PyPI: pip install spotify-bulk-actions-mcp - but you'll still need local .env and auth setup.

3. Authenticate with Spotify (One-Time)

This opens a browser for you to log in:

python setup_auth.py

After login, your token is saved locally in .spotify_cache/.

4. Test It Works

source venv/bin/activate
python -c "from src.utils.auth import is_authenticated; print('Auth OK!' if is_authenticated() else 'Not authenticated')"

5. Connect to Claude Code

Add this to your Claude Code settings (~/.claude/settings.local.json):

{
  "mcpServers": {
    "spotify": {
      "command": "/path/to/spotify-bulk-actions-mcp/venv/bin/python",
      "args": ["/path/to/spotify-bulk-actions-mcp/src/server.py"]
    }
  }
}

Restart Claude Code after adding this.

Available Tools (18)

Library Analysis

Tool Description
check_auth_status Verify Spotify auth is working
get_followed_artists Get all artists you follow
get_saved_tracks Get all your liked songs
get_library_artists Artists from saved songs, ranked by count
get_albums_by_song_count Albums with N+ saved songs
export_library_summary Complete library export

Search

Tool Description
search_track Search for a single track
search_track_fuzzy Broader search when exact fails
batch_search_tracks Search many tracks with confidence scores
get_track_preview_url Get 30-second preview URL

Playlists

Tool Description
create_playlist Create a new playlist
add_tracks_to_playlist Add tracks to existing playlist
import_and_create_playlist Full CSV → playlist workflow
create_playlist_from_search_results Create from batch search
add_reviewed_tracks Add reviewed/corrected tracks
get_playlist_info Get playlist details

Utilities

Tool Description
parse_song_list_csv Validate a song CSV
export_review_csv Export uncertain matches for review

Example Workflows

Get Your Library Stats

Ask Claude:

"What artists do I have the most saved songs from?"

Claude will use get_library_artists and show you.

Find Albums for Vinyl

Ask Claude:

"Find albums where I have 6 or more saved songs"

Claude will use get_albums_by_song_count with min_songs=6.

Create Playlist from Song List

  1. Create a CSV file:
title,artist
Bohemian Rhapsody,Queen
Hotel California,Eagles
Billie Jean,Michael Jackson
  1. Ask Claude:

"Create a playlist called 'My Mix' from this CSV: [paste CSV]"

Claude will:

  1. Parse the CSV
  2. Search each song with confidence scoring
  3. Create the playlist with high-confidence matches
  4. Show you uncertain matches to review

Bulk Podcast Playlist

For large lists (500+ songs):

  1. Ask Claude to use batch_search_tracks with your song list
  2. Review the results (HIGH goes in automatically)
  3. Use export_review_csv to get uncertain matches
  4. Review/correct in a spreadsheet
  5. Use add_reviewed_tracks to add your corrections

Rate Limits

The server handles Spotify's rate limits automatically:

  • Small delays between API calls
  • Automatic retry on 429 errors
  • Caching to reduce repeat calls

For 10k songs, expect the initial library fetch to take 2-3 minutes.

Files & Data

Location Purpose
.env Your Spotify credentials (gitignored)
.spotify_cache/ Auth tokens and cached data (gitignored)
src/server.py Main MCP server
src/tools/ Tool implementations

Troubleshooting

"Not authenticated" error:

python setup_auth.py

Rate limit errors: Wait a few minutes and try again. The server will auto-retry.

Token expired: The server auto-refreshes tokens. If issues persist, re-run setup_auth.py.

Security Notes

  • Your credentials are in .env (gitignored, never committed)
  • Auth tokens are stored locally in .spotify_cache/
  • Never share your .env or token files
  • If credentials are exposed, rotate them in Spotify Dashboard

License

MIT


Made cause I can't not have headphones on. If this helps you, buy me a coffee!

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured