Last.fm MCP for AI. Audit Music History with Conversational AI
Works with every AI agent you already use
…and any MCP-compatible client








Connect to your AI in seconds.
Last.fm connects your AI client to global music listening data. Use this MCP to audit scrobbling history, track top artists and albums, and retrieve detailed metadata for any song or artist.
It turns complex musical statistics into simple conversational queries for your agent.
What your AI can do
Get album info
Gets metadata for a specific album, including its details and tracklist.
Get artist info
Retrieves detailed background information about any given musical artist.
Get loved tracks
Lists the songs that a user has marked as their favorites or 'loved' tracks.
Get a list of all songs and artists the user has recently listened to over various timeframes.
Determine a user's most-played tracks, albums, or artists at any point in their listening history.
Fetch deep background information on specific songs, albums, or artists.
Access top-rated music tags and charts to see what genres are popular worldwide right now.
Pull core user account information, letting you manage or verify profile details through the agent.
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Last.fm: 10 Tools for Music Data
These tools let your AI client pull specific music data, from user profiles to global genre trends, using dedicated functions.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Last.fm on VinkiusGet Album Info
Gets metadata for a specific album, including its details and tracklist.
Get Artist Info
Retrieves detailed background information about any given musical artist.
Get Loved Tracks
Lists the songs that a user has marked as their favorites or 'loved' tracks.
Get Recent Tracks
Provides a list of the most recently played songs by the connected user.
Get Top Albums
Shows the top albums that a user has listened to over time.
Get Top Artists
Determines and lists the most popular artists for the connected user.
Get Top Tags
Retrieves a list of trending music tags across the platform, useful for spotting genre shifts.
Get Top Tracks
Lists and ranks the songs that have been streamed most frequently by the user.
Get Track Info
Fetches all available metadata for a single, specific song or track.
Get User Info
Gathers basic and detailed information about the connected Last.fm user account.
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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 connection provides 10 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
Manually compiling music data is a painful process.
Right now, if you need to audit listening habits for research, you're stuck clicking across multiple websites. You check the main site for top artists, then jump to another dashboard to see recent songs, and finally use a third tab just to pull metadata on one specific album. It’s copy-pasting names into spreadsheets all day.
With this MCP, your agent handles the whole chain. Instead of clicking through dashboards, you ask it one question. You get structured data covering everything from `get_top_artists` lists to detailed track info—all returned immediately.
Get precise music metadata with Last.fm MCP
You no longer have to manually search for a song's origin or its full list of contributors. If you know the artist and album, calling `get_album_info` provides all that structured data in one go.
The difference is speed and completeness. You get actionable metadata instantly, letting you focus on analysis instead of API calls.
What your AI can actually do with this
Your agent can build a complete picture of personal and global music taste without you needing to open a dashboard. Instead of manually navigating menus and filtering dates, your AI client handles the whole process through natural conversation. You ask for top artists from last quarter, or the full metadata for a specific track, and it just works.
The system pulls that data directly into your workflow. Since Vinkius hosts this MCP within its catalog, you connect once from any compatible agent, giving you access to deep music analysis tools right where you're coding or writing.
This means whether you’re tracking a friend’s listening habits for a project or just curious about the genre trends of your favorite decade, you get instant, quantified results. You audit everything—from listing recent tracks played to understanding an artist's entire catalog metadata.
019d8451-c7d0-7324-a36a-746b233c57d2 Here's how it actually works
The bottom line is you get real-time, auditable music statistics without ever leaving your coding environment.
First, subscribe to this MCP and provide your Last.fm API key credentials.
Next, prompt your AI client with a natural language query (e.g., 'Show me my top 10 tracks last month').
Your agent executes the necessary tool calls against the music data and returns structured results directly into your chat or script.
Who is this actually for?
Music journalists, content curators, and data analysts use this. They're tired of switching between Spotify for listening and Google Sheets for stats. This MCP puts the whole audit process into a single conversation.
Uses it to verify if new tracks or artists fit established trends by checking top tags and retrieving metadata.
Runs deep audits on user profiles, pulling recent tracks and loved tracks across different time periods for articles.
Retrieves top artists and albums to build quantitative reports on user behavior and genre popularity shifts.
What Changes When You Connect
Get immediate data on top tracks and artists. Instead of checking a dashboard, your agent just lists out the top 5 songs or the biggest artist for you.
Track musical trends easily. Use get_top_tags to see what genres are trending globally, which is faster than manually browsing charts.
Deep dive into content. Need to verify details on a specific album? Just call get_album_info, and your agent returns the metadata instantly.
Audit user behavior quickly. With tools like get_recent_tracks and get_loved_tracks, you can reconstruct listening history for reporting or research.
Keep everything in one place. By connecting this MCP through Vinkius, you keep music data querying alongside your other operational tasks.
See it in action
Analyzing a Friend's Taste
A marketing intern wants to send a personalized birthday message based on the recipient’s favorite artists. They ask their agent: 'What are user X's top 5 artists and what did they listen to last month?' The agent uses get_top_artists and get_recent_tracks to gather actionable data.
Researching Genre Shifts
A music blogger needs proof of a genre's decline. They ask the agent to check global trends by running get_top_tags. The agent retrieves the latest tags, allowing the blogger to write an article on current musical tastes.
Cross-referencing Album Details
A record label employee needs to confirm a release date or genre for a specific album. They run get_album_info using the album title, getting all the necessary metadata without calling any external databases.
Building a Recommendation Engine
A developer wants to build an app that recommends music based on current favorites. The agent first runs get_user_info and then uses get_loved_tracks to pull the core dataset for the recommendation logic.
The honest tradeoffs
Trying to query everything at once
A user might ask, 'Give me all my music data: top tracks, albums, and artists.' This vague request forces the agent to guess which specific tools are needed.
Break it down. First, run get_top_artists for a list of names. Then, call get_loved_tracks using those artist IDs to get the associated songs.
Forgetting time context
Asking only 'What were my top tracks?' without specifying a timeframe. The agent might return general lifetime stats instead of what you need for this quarter.
Always specify the date range in your prompt, or use tools that accept relative timeframes like get_recent_tracks.
Only asking about the user
Asking 'What are my favorite songs?' but failing to provide enough context. The agent might not know if you mean all-time favorites or just last week's.
Use get_loved_tracks for general favorites, then follow up with a time constraint like checking the top tracks from the last 30 days.
When It Fits, When It Doesn't
Use this MCP if your core need is to audit structured music consumption data. If you want to know what was played and who made it popular, this is key. Don't use it just because you need general content ideas; for that, check a dedicated trend-forecasting tool. Only rely on get_top_tags if you are interested in broad genre metrics—it won't give you personal listening history. If your goal is to write a biography or analyze an artist's career arc, start with get_artist_info first; it provides the necessary context before running detailed reports using get_album_info.
Questions you might have
How do I use the `get_user_info` tool with Last.fm? +
You simply ask your agent to retrieve user details. This tool fetches general account information, which helps you verify or manage basic profile credentials within your workflow.
What is the difference between `get_top_tracks` and `get_recent_tracks`? +
get_recent_tracks shows a chronological list of everything played. In contrast, get_top_tracks ranks songs based on their total play count over the defined period.
Can I find out about an artist's whole history using `get_artist_info`? +
Yes, this tool retrieves comprehensive background metadata for any artist. It gives you enough detail to build a solid profile summary for writing or research.
Do I need multiple tools to see my loved tracks? Use `get_loved_tracks`. +
No, just use the dedicated get_loved_tracks function. It isolates your favorited songs and returns them in a clean list for you.
What's the best way to check global music trends? Use `get_top_tags`. +
get_top_tags is designed specifically for this. It bypasses personal history and shows current, trending genre tags across the entire platform.
If I use `get_album_info` with an unknown album ID, how do I handle the failure? +
The tool returns specific error codes in the response payload. Your agent should check for standard API status messages like 'Not Found' rather than assuming a request failed silently.
Are there any limits on data when running `get_top_artists`? +
Yes, rate limiting applies to large queries. For full datasets, your agent must look for pagination tokens in the response payload to pull all available results across multiple calls.
What metadata does `get_track_info` return so I can build a complete record? +
It delivers core data points like duration, explicit tags, and source information. This depth lets your agent create detailed records without needing to make extra calls.
How do I find my Last.fm API Key? +
Go to the Last.fm API account page, create an API account, and you will find your API Key there. Copy and paste it into the field below.
Can the agent check my top artists for a specific period? +
Yes. Use the get_top_artists tool providing your username and the desired period (e.g., 'overall', '7day', '1month'). Your agent will return your most-listened artists instantly.
Is it possible to retrieve metadata for a specific track via the agent? +
Yes. The get_track_info tool allows your agent to fetch complete metadata for any song by providing the artist and track names, including album and listener counts.
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