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Jamendo MCP. Find, filter, and manage music metadata instantly.

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Jamendo MCP on Cursor AI Code Editor MCP Client Jamendo MCP on Claude Desktop App MCP Integration Jamendo MCP on OpenAI Agents SDK MCP Compatible Jamendo MCP on Visual Studio Code MCP Extension Client Jamendo MCP on GitHub Copilot AI Agent MCP Integration Jamendo MCP on Google Gemini AI MCP Integration Jamendo MCP on Lovable AI Development MCP Client Jamendo MCP on Mistral AI Agents MCP Compatible Jamendo MCP on Amazon AWS Bedrock MCP Support

Just plug in your AI agents and start using Vinkius.

Jamendo MCP Server connects your AI agent to a massive catalog of independent music. Use it to search, filter, and discover tracks by mood, genre, or geographical location.

Find album metadata, retrieve similar songs for perfect recommendations, and manage user favorites—all through natural conversation.

What your AI agents can do

Autocomplete search

Suggests tracks, albums, artists, or tags as you type a search query.

Get album reviews

Retrieves and filters community reviews for a specific album.

Get album tracks

Pulls a list of all tracks belonging to an identified album.

+ 22 more capabilities included
Search and Filter Tracks

Find music using keywords, specific tags, or filters like speed (high/low) and vocal type via search_tracks.

Research Artists and Albums

Get detailed metadata for artists (get_artist_albums, get_artist_tracks), including their locations, reviews, and discography.

Discover Related Music

Find similar tracks to a given ID using get_similar_tracks or find curated collections by searching playlists with search_playlists.

Manage User Preferences

Automatically track user interaction history, allowing you to retrieve lists of liked tracks (set_user_like) or albums (get_user_albums).

Explore Radio & Feeds

List available radio stations using list_radios and pull editorial content from the homepage via get_feeds.

Supported MCP Clients

Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel
+ other MCP clients
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AI Agent

Jamendo MCP Server: 25 Tools for Music Discovery

These tools let your AI client interact with every facet of the Jamendo music catalog—from searching specific tags to managing user favorites.

autocomplete019e5d28

autocomplete search

Suggests tracks, albums, artists, or tags as you type a search query.

get019e5d28

get album reviews

Retrieves and filters community reviews for a specific album.

get019e5d28

get album tracks

Pulls a list of all tracks belonging to an identified album.

get019e5d28

get artist albums

Lists all albums released by a specific artist.

get019e5d28

get artist locations

Filters and retrieves artists based on their recorded geographical location.

get019e5d28

get artist tracks

Retrieves a list of all tracks associated with a specific artist.

get019e5d28

get feeds

Grabs editorial content and news headlines from the Jamendo homepage.

get019e5d28

get playlist tracks

Gets all the individual tracks that are contained within a user-defined playlist.

get019e5d28

get radio stream

Provides the stream URL and details for an active radio station.

get019e5d28

get similar tracks

Finds tracks that sound stylistically similar to a provided track ID.

get019e5d28

get track reviews

Retrieves and filters community reviews written for a specific song.

get019e5d28

get user albums

Lists albums that the current user has interacted with or saved.

get019e5d28

get user artists

Retrieves a list of artists the current user has shown interest in.

get019e5d28

get user tracks

Lists all tracks that the current user has interacted with or saved to their profile.

get019e5d28

get users

Looks up basic public profile information for a given user account.

list019e5d28

list radios

Provides a list of all available radio stations on the platform.

search019e5d28

search albums

Searches and filters the overall catalog of music albums.

search019e5d28

search artists

Searches and filters artists by name or genre keywords.

search019e5d28

search playlists

Finds public or private playlists based on keywords or criteria.

search019e5d28

search tracks

Performs the main search across the entire track catalog, supporting tags and speed filters.

set019e5d28

set user dislike

Marks a specific track as disliked by the user account (requires token).

set019e5d28

set user fan

Designates an artist as a fan of the user account (requires token).

set019e5d28

set user favorite

Adds a track to the user's private list of favorites (requires token).

set019e5d28

set user like

Marks a specific track as liked by the user account (requires token).

set019e5d28

set user playlist

Creates or updates a playlist in the system with new tracks and settings (requires token).

Choose How to Get Started

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What you can do with this MCP connector

Listen up. This server isn't just another API connection; it’s your AI agent's backstage pass to Jamendo’s entire music library. You connect your client—Claude, Cursor, whatever you use—and suddenly, a massive catalog of independent, royalty-free tracks is right at your fingertips. Forget learning complex query languages or dealing with endless web forms.

Your agent handles the dirty work; you just talk about what you wanna hear.

Search and Discovery: Finding What You Need Fast

You gotta find music, right? When you start typing a search query, autocomplete_search suggests tracks, albums, artists, or tags instantly. That cuts down on wasted time big time. For deep dives, you've got search_tracks, which is the main event here; you can filter by keywords, specific tags, or even technical stuff like speed (high/low) and vocal type, so you don’t end up with random noise.

If you know an artist, search_artists lets you pinpoint them by name or genre. Similarly, search_albums filters the whole catalog down to albums, while search_playlists finds public or private collections based on keywords.

Researching Talent and Metadata

Want to dig into an artist? You can pull a list of every album they've put out using get_artist_albums. And you don't just get the titles; you get the tracks. get_artist_tracks pulls all their individual songs, and if you need everything on one specific record, get_album_tracks lists every track inside that album.

Need to know where they came from? Use get_artist_locations to filter artists by recorded geographical location. When the music itself is the star, you've got tools for context: get_similar_tracks finds songs that sound stylistically close to a track ID you give it, and if you wanna check out what people think of something specific, you can grab community reviews using get_album_reviews or get_track_reviews.

Managing Your Listening History and Preferences

Your agent keeps track of your taste. You've got tools to manage that data point by point. When you find a track you dig, you can mark it with your client using set_user_like, or if it’s trash, use set_user_dislike. To save tracks for later, simply call set_user_favorite and add it to your private list.

You can also build out whole collections with set_user_playlist, which either creates a new playlist or updates an existing one with specific tracks and settings. Your history is always accessible: you can pull up all the albums you've saved using get_user_albums, check out artists you're interested in via get_user_artists, or see every track you've interacted with by running get_user_tracks.

Exploring Ambient Content and Radio

Sometimes you don't know what you want. That's fine. You can pull editorial content and news headlines from the homepage using get_feeds. If you just wanna put on some background noise, list_radios gives you every available radio station, and then get_radio_stream hands you the stream URL and details for whatever station you pick.

Plus, if a user is already listening to something, your agent can get all those individual tracks contained within a whole playlist using get_playlist_tracks. Finally, you can look up basic public profile info on any account using get_users.

The Bottom Line

Your AI client uses these tools in sequence. You tell it what you want—'Find me some high-speed instrumental rock from Paris that sounds like track X.' Your agent runs the necessary calls: maybe search_tracks first, then checks locations with get_artist_locations, and finally compares the sound using get_similar_tracks. It’s all natural conversation.

No coding required.

How Jamendo MCP Works

  1. 1 Subscribe to this server on Vinkius Marketplace and enter your Jamendo Client ID.
  2. 2 Your AI client sends a natural language request (e.g., 'Find me upbeat jazz tracks').
  3. 3 The agent translates the query into multiple tool calls (search_tracks, get_artist_locations) and delivers structured metadata.

The bottom line is, your AI acts as a personal music librarian that handles all the messy search logic for you.

Who Is Jamendo MCP For?

Content creators who need constant background audio without licensing headaches. Developers integrating music discovery into a larger application stack. Music librarians or researchers mapping regional musical trends.

Content Creator

Needs to find royalty-free tracks quickly for videos, filtering by mood tags and instrumental type.

Software Developer

Integrates music metadata retrieval into a backend service; needs to call tools like get_artist_tracks and validate data structures.

Music Researcher/Curator

Maps the geographical spread of independent talent, using get_artist_locations to build regional indexes.

What Changes When You Connect

  • Stop manually searching. Use search_tracks to find tracks based on specific criteria like 'high-speed' or 'instrumental,' cutting search time from minutes to seconds.
  • Deep dive into artist research. Instead of checking multiple pages, ask your agent to run get_artist_albums and get_artist_locations together to map an artist’s entire global footprint.
  • Build smarter recommendation engines. Pass a track ID to get_similar_tracks, and instantly get metadata for tracks that match the style—essential for playlist generation tools.
  • Manage user data without boilerplate code. Use set_user_like or set_user_favorite to log activity directly, feeding clean preference data into your application logic.
  • Streamline content prep. Your agent can fetch news (get_feeds), search playlists (search_playlists), and grab tracks all in one conversation, eliminating context switching.

Real-World Use Cases

01

Creating a Mood-Based Playlist

A content creator needs background music for an 'epic sunrise' video. Instead of browsing by genre, they ask their agent: 'Find high-speed instrumental tracks with the tag 'uplifting'. The agent runs search_tracks and returns a list of track IDs that can be fed into a user playlist via set_user_playlist.

02

Auditing Artist Market Reach

A music label needs to know where an artist is most popular. They ask their agent to run get_artist_locations for the target artist, which immediately filters and lists all recorded geographical spots.

03

Building a Recommendation Widget

A streaming platform wants to suggest music based on what's currently playing. They pass the current track ID to get_similar_tracks, getting a list of metadata that powers their 'You might also like' widget.

04

Analyzing User Taste History

A platform owner needs to know what genres users prefer over time. They ask the agent to aggregate data from get_user_albums and get_user_tracks, giving them a clear view of past consumption.

The Tradeoffs

Trying to search everything at once

Asking the agent: 'Give me all music, artists, and playlists related to jazz in Paris.' This is too vague for a tool call.

Break it down. First, use search_artists with keywords ('Jazz'). Then, refine location using get_artist_locations. Finally, find albums using get_album_tracks.

Assuming track IDs are universal

Passing a random ID from another service to get_similar_tracks, causing the API call to fail.

Always verify the source of your track ID. If you don't have it, use search_tracks first to generate a valid Jamendo ID.

Ignoring user permissions

Attempting to run set_user_favorite without providing the necessary OAuth2 access token.

Remember that tools like setting likes (set_user_like) require authentication. Ensure your agent has the required scope and token.

When It Fits, When It Doesn't

Use this server if your core problem is discovery or metadata aggregation. Specifically, if you need to combine location data with music history, or find related tracks based on a starting point (get_similar_tracks), this is the right tool. You're building out a recommendation engine or a deep research portal.

Don't use it if all you need is simple CRUD operations (Create/Read/Update/Delete) on pre-existing data that isn't related to music. If your flow is just 'fetch X and display Y,' a dedicated, lightweight API might be simpler than using the full MCP graph. Use this when the relationships between Artist, Album, Track, and Location are as important as the data itself.

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Jamendo. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Works with Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This server provides 25 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.

Available Capabilities

autocomplete_search get_album_reviews get_album_tracks get_artist_albums get_artist_locations get_artist_tracks get_feeds get_playlist_tracks get_radio_stream get_similar_tracks get_track_reviews get_user_albums get_user_artists get_user_tracks get_users list_radios search_albums search_artists search_playlists search_tracks set_user_dislike set_user_fan set_user_favorite set_user_like set_user_playlist

Sifting through music libraries used to feel like clicking through endless folder structures.

Before having an agent, building a content library meant dozens of manual clicks. You'd search for 'ambient rock,' hit the results, then click an artist, check their albums, and if those weren't right, you had to go back up and try filtering by mood tags or geographical origin—a huge waste of time.

Now, your agent handles that mess. Just tell it: 'I need high-speed instrumental music from Seattle.' It runs `search_tracks` filtered by speed *and* location (`get_artist_locations`), giving you the perfect list in one go.

Getting similar tracks with get_similar_tracks

Previously, if a user loved 'Ocean Breeze,' you had to manually listen through dozens of recommended songs until you found something that hit the right vibe. It was guesswork.

Now, your agent uses `get_similar_tracks` on the track ID. It analyzes the style and tempo instantly, giving you 5 guaranteed options that match the user's taste profile.

Common Questions About Jamendo MCP

How do I search for tracks by mood or speed using search_tracks? +

You pass specific parameters like 'speed: high' and 'tag: rock' directly to search_tracks. You don't need separate calls; the tool handles all the filtering logic.

Can I use get_artist_locations for more than just one country? +

Yes, you can filter artists by multiple locations in a single query. This is useful if your research spans several distinct regions or continents.

Do I need to call search_tracks before using get_similar_tracks? +

No. get_similar_tracks requires only the track ID itself. However, if you don't know the ID, run search_tracks first; that will give you a valid candidate ID.

How does set_user_like work with my account? +

The set_user_like tool requires an OAuth2 access token to identify which user is liking the track. You must ensure your agent has the necessary write permissions.

How do I use `get_user_albums` to see my history? +

It requires an active OAuth2 access token. The server uses this token to identify your account and pull only the albums you've interacted with, keeping your data private.

What happens if I use bad inputs in `search_tracks`? +

The API returns a detailed error code and message. You need to check the documentation for required parameters; for example, speed must be one of 'high', 'medium', or 'low'.

Can I chain `get_artist_albums` results into `get_album_tracks`? +

Yes, you can link these tools. Take the Album ID returned from get_artist_albums, and use that specific ID to feed get_album_tracks. This pulls all tracks belonging to that album.

Are there rate limits when calling `list_radios`? +

The endpoint is subject to standard API rate limiting. If you exceed the allowed calls, your agent will receive a 429 error. You'll need to wait about a minute before retrying.

Can I search for music based on specific moods or technical attributes like speed? +

Yes! Use the search_tracks tool with parameters like tags for mood and speed (high, medium, low) to filter the catalog exactly how you need.

How do I find artists from a specific city or country? +

You can use the get_artist_locations tool. Simply provide the location_country (code) or location_city to see a list of artists from that area.

Is it possible to get recommendations based on a track I like? +

Absolutely. Use the get_similar_tracks tool with the ID of the track you like, and the agent will return a list of musically similar tracks from the Jamendo library.

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