Navidrome▌
by blakeem
Navidrome server streamer for complete music library management with playlists, playback, search, radio, lyrics & Last.f
Integrates with Navidrome music servers to provide complete music library management including playlist creation, playback control, search functionality, listening history tracking, Last.fm integration for recommendations, Radio Browser for internet radio discovery, and LRCLIB for synchronized lyrics retrieval.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Self-hosted music enthusiasts with Navidrome servers
- / Creating AI-curated playlists from personal libraries
- / Music discovery and recommendation workflows
capabilities
- / Browse and search your music library
- / Create and manage playlists
- / Control music playback
- / Track listening history and analytics
- / Get Last.fm music recommendations
- / Find internet radio stations
- / Retrieve synchronized lyrics
what it does
Connects AI assistants to your Navidrome music server for natural language control of your personal music library. Create playlists, search music, control playback, and discover new content through conversation.
about
Navidrome is a community-built MCP server published by blakeem that provides AI assistants with tools and capabilities via the Model Context Protocol. Navidrome server streamer for complete music library management with playlists, playback, search, radio, lyrics & Last.f It is categorized under other, analytics data.
how to install
You can install Navidrome 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.
license
AGPL-3.0
Navidrome is released under the AGPL-3.0 license.
readme
Navidrome MCP Server
Transform your Navidrome music server with an AI-powered music assistant. This MCP (Model Context Protocol) server enables Claude, ChatGPT, and other AI assistants to interact with your personal music library through natural language, offering intelligent playlist creation, music discovery, and library management.
Table of Contents
- Why Navidrome MCP?
- Features
- Installation
- Powerful Usage Examples
- Available Tools
- Troubleshooting
- Development
- License
Why Navidrome MCP?
Imagine having an AI assistant that truly understands your music taste. This MCP server enables AI assistants to:
- Analyze your listening patterns and create perfectly curated playlists
- Discover hidden gems in your library based on your mood or activity
- Build custom radio stations from your favorite tracks
- Find music similar to what you love using Last.fm's recommendation engine
- Discover internet radio stations from around the world with advanced filtering
- Get synchronized lyrics with millisecond-precision timestamps for your favorite tracks
- Manage your library with simple conversational commands
This isn't just another music tool – it's your personal music curator powered by AI.
Features
🎵 Music Library Management
- Intelligent Browsing: Navigate songs, albums, artists, and genres with smart filtering
- Deep Search: Full-text search across all metadata or targeted searches for specific content
- Rich Metadata: Access detailed information about tracks, albums, and artists
- Tag Analysis: Explore and analyze metadata tags (genre, composer, label, year, and more)
- Clean Responses: Optimized data transfer with only essential fields (~10 properties vs 50+ raw)
🎶 Intelligent Playlist Creation
- AI Assistant Integration: Enables AI assistants to analyze your taste and build themed playlists
- Smart Management: Create, update, and organize playlists conversationally
- Flexible Track Addition: Add songs by ID, entire albums, artist discographies, or specific discs
- Dynamic Reordering: Rearrange tracks with simple commands
- Cross-Reference: Find which playlists contain specific songs
🎼 Personalized Music Discovery
- Listening Data Access: Provides listening history data for AI assistants to understand your preferences
- Similar Artist/Track Finding: Discover music similar to your favorites via Last.fm
- Artist Deep Dives: Get biographies, popular tracks, and related artists
- Global Trends: Browse worldwide music charts and trending genres
- Library Analysis Tools: Access data to help AI assistants find overlooked tracks in your library
📻 Smart Radio Management
- Stream Validation: Test radio URLs before adding to avoid broken streams
- Format Detection: Automatic detection of MP3, AAC, OGG, FLAC streams
- Metadata Extraction: Pull station info from SHOUTcast/Icecast headers
- Custom Station Creation: Build radio stations from your collection
- One-Time Setup Tips: Smart contextual help that appears only when needed
🌍 Internet Radio Discovery
- Global Station Database: Access thousands of internet radio stations worldwide via Radio Browser
- Advanced Filtering: Search by genre, country, language, codec, bitrate, and more
- Automatic Validation: Discovered stations are tested for availability
- Quality Control: Filter out broken stations and focus on high-quality streams
- Popularity Metrics: Discover stations by vote count and listener engagement
- Station Management: Tools for AI assistants to add discovered stations to your collection
🎤 Synchronized Lyrics
- Time-Synchronized Lyrics: Get lyrics with millisecond-precision timestamps for line-by-line timing
- Dual Format Support: Access both time-synced and plain text lyrics
- Community-Powered: Lyrics sourced from LRCLIB's community database
- Smart Matching: Automatic matching by title, artist, album, and duration
- No API Keys Required: Free lyrics access without registration
📊 Analytics & Insights
- Listening Patterns: Understand your music habits with play statistics
- Taste Evolution: Track how your preferences change over time
- Most/Least Played: Discover your true favorites and forgotten tracks
- Genre Distribution: Access data about your library's composition for analysis
- Recommendation Data: Provides data for AI assistants to generate suggestions based on your history
⭐ Preference Management
- Star System: Mark favorites for quick access
- 5-Star Ratings: Rate content for better recommendations
- Queue Control: Manage playback queues across devices
- Data Access for Organization: Provides preference data for AI assistants to help organize your collection
Installation
Prerequisites
- Node.js 20+ (Download here)
- Running Navidrome server with your music library
- Claude Desktop or ChatGPT Desktop (or any MCP-compatible client)
Additional for manual build:
- pnpm package manager (Install instructions)
Quick Setup
Method 1: NPM Package (Recommended)
The easiest way to get started is using the published npm package, which auto-updates on launch:
npm install -g navidrome-mcp
📦 Package: navidrome-mcp on npm
This installs the MCP server globally and keeps it up-to-date automatically.
Method 2: Manual Build (Development)
For development or custom builds:
git clone https://github.com/Blakeem/Navidrome-MCP.git
cd navidrome-mcp
pnpm install
pnpm build
Configure Claude Desktop
Find your configuration file:
- Windows:
%APPDATA%/Claude/claude_desktop_config.json - macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Linux:
~/.config/Claude/claude_desktop_config.json
Add the Navidrome MCP server:
Using NPM Package (Recommended)
{
"mcpServers": {
"navidrome": {
"command": "npx",
"args": ["navidrome-mcp"],
"env": {
"NAVIDROME_URL": "http://your-server:4533",
"NAVIDROME_USERNAME": "your_username",
"NAVIDROME_PASSWORD": "your_password",
"NAVIDROME_DEFAULT_LIBRARIES": "1,2", // Optional: Set default active libraries (comma-separated IDs)
"LASTFM_API_KEY": "your_api_key", // Get your own at https://www.last.fm/api/account/create
"RADIO_BROWSER_USER_AGENT": "Navidrome-MCP/1.0 (+https://github.com/Blakeem/Navidrome-MCP)",
"LYRICS_PROVIDER": "lrclib",
"LRCLIB_USER_AGENT": "Navidrome-MCP/1.0 (+https://github.com/Blakeem/Navidrome-MCP)"
}
}
}
}
Using Manual Build (Alternative)
{
"mcpServers": {
"navidrome": {
"command": "node",
"args": ["/absolute/path/to/navidrome-mcp/dist/index.js"],
"env": {
"NAVIDROME_URL": "http://your-server:4533",
"NAVIDROME_USERNAME": "your_username",
"NAVIDROME_PASSWORD": "your_password",
"NAVIDROME_DEFAULT_LIBRARIES": "1,2", // Optional: Set default active libraries (comma-separated IDs)
"LASTFM_API_KEY": "your_api_key", // Get your own at https://www.last.fm/api/account/create
"RADIO_BROWSER_USER_AGENT": "Navidrome-MCP/1.0 (+https://github.com/Blakeem/Navidrome-MCP)",
"LYRICS_PROVIDER": "lrclib",
"LRCLIB_USER_AGENT": "Navidrome-MCP/1.0 (+https://github.com/Blakeem/Navidrome-MCP)"
}
}
}
}
Important:
- NPM method: Uses
npx navidrome-mcpwhich auto-updates on each launch - Manual method: Requires absolute paths (full path from root) and manual updates
- Library filtering: Use
NAVIDROME_DEFAULT_LIBRARIESto set default active libraries (e.g., "1" for one library, "1,2,3" for multiple)- If not set, all libraries are active by default
- You can change active libraries at runtime using the
set_active_librariestool - Invalid library IDs are ignored with a warning
- Get a free Last.fm API key at Last.fm (optional - enables music discovery)
- Radio Browser integration requires a User-Agent string (enables station discovery)
- Lyrics integration works without API keys (LRCLIB is free)
- Features are automatically enabled/disabled based on available configuration
- Restart Claude Desktop after saving
Configure ChatGPT Desktop
Using NPM Package (Recommended)
- Open ChatGPT Desktop
- Go to Settings → Connectors
- Click Create and add:
- Command:
npx - Args:
navidrome-mcp - Environment variables: Same as above
- Command:
- Save and restart
Using Manual Build (Alternative)
- Open ChatGPT Desktop
- Go to Settings → Connectors
- Click Create and add:
- Command:
node - Args:
/absolute/path/to/navidrome-mcp/dist/index.js - Environment variables: Same as above
- Command:
- Save and restart
Powerful Usage Examples
🎯 Smart Discovery & Playlist Creation
- "Look at my most played artists, find what albums I'm missing from their discographies, and tell me which ones are most popular"
- **"Create a 'Best of Pink Floyd' playlist using Last.fm's top tracks data, but only with so
FAQ
- What is the Navidrome MCP server?
- Navidrome is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Navidrome?
- This profile displays 70 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
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
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
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
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ 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.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.6★★★★★70 reviews- ★★★★★Olivia Kim· Dec 16, 2024
Useful MCP listing: Navidrome is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Charlotte Srinivasan· Dec 12, 2024
Navidrome is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Olivia Park· Dec 4, 2024
I recommend Navidrome for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Jin Li· Nov 23, 2024
Navidrome is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Kiara Flores· Nov 11, 2024
According to our notes, Navidrome benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Ren Harris· Nov 7, 2024
We wired Navidrome into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Ren Martin· Nov 7, 2024
Navidrome reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Henry Thomas· Nov 3, 2024
I recommend Navidrome for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Min Abebe· Nov 3, 2024
We wired Navidrome into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Olivia Huang· Oct 26, 2024
According to our notes, Navidrome benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
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