Introduction: When Your Music Data Should Belong to You
Let's be honest—if you're the type of person who cares about tracking every song you listen to, you're probably already using Last.fm. Or maybe you tried it years ago and got frustrated when they changed their API, limited features, or just... well, stopped innovating. I've been there. I've watched my meticulously curated listening data live on someone else's servers, subject to their business decisions and privacy policies. That's why when Koito v0.1.3 dropped in early 2026, it felt like someone finally built the tool I'd been wishing for.
Koito isn't just another scrobbler. It's a complete, self-hosted ecosystem for obsessing over your music listening habits. And the recent v0.1.3 release? It addresses nearly every concern raised by the self-hosted community when the project first launched seven months ago. From that slightly awkward name clarification (no, it's not what you think in Spanish or Portuguese) to robust Docker support and actual working mobile apps, this update transforms Koito from a promising experiment into a legitimate alternative to commercial services.
The Self-Hosted Scrobbling Revolution: Why Now?
Music data collection has always been a weird space. Services like Last.fm pioneered the concept of "scrobbling" (basically, automatically tracking what you play) back in the early 2000s. For years, they were the only game in town. But here's the thing—as our awareness of data privacy has grown, and as streaming services have become more walled gardens, the limitations of centralized scrobbling services have become painfully apparent.
I've talked to dozens of music enthusiasts who've expressed the same frustrations: "I lost years of data when they changed their API," "The recommendations got worse over time," "I don't trust what they're doing with my listening habits." These aren't niche concerns. They're fundamental issues with the model of handing over your personal cultural consumption data to a corporation.
Enter the self-hosted movement. Over the past five years, we've seen an explosion of tools that let people reclaim control over their digital lives. From photo storage to password managers to—yes—music tracking. The timing is perfect. With containerization making deployment trivial and modern web technologies creating beautiful interfaces, building your own scrobbling infrastructure is no longer just for hardcore developers.
Koito v0.1.3: What Actually Changed?
The original Koito announcement seven months ago generated serious buzz in r/selfhosted (591 upvotes and 149 comments tells you something). But like any early-stage project, it had rough edges. The community feedback was extensive and specific. Developers asked about Docker Compose support. Mobile users wondered about iOS and Android apps. Privacy-conscious folks questioned data storage and retention policies.
Version 0.1.3 directly addresses these concerns. First, the Docker situation is now properly documented and actually works out of the box. No more wrestling with permissions or mysterious container failures. The mobile apps—which were basically proof-of-concepts before—now reliably sync with your self-hosted instance. There's even preliminary Plex integration, which was a huge request from media server enthusiasts.
But here's what really impressed me: the data export features. One of the most common complaints about Last.fm is how hard it is to get your data out. Koito now offers multiple export formats (JSON, CSV, even SQLite dumps) with a clean interface. You own your data, and you can actually do something with it. That's the promise of self-hosting made real.
Setting Up Koito: The Practical Guide
Let's get concrete. Installing Koito v0.1.3 is straightforward if you're familiar with Docker, but I'll walk through the key steps because there are a few gotchas. First, you'll need Docker and Docker Compose installed on your server or NAS. The project's documentation has improved dramatically, but I've found a few optimizations they don't mention.
Start by cloning the repository. The docker-compose.yml file is well-commented, but pay attention to the volume mounts. I recommend creating a dedicated directory for Koito's data (something like /opt/koito/data) rather than using the default relative paths. It makes backups easier. The PostgreSQL container is included, which is nice—no external database setup required.
Once running, the web interface is accessible on port 3000. The initial setup wizard guides you through creating an admin account and connecting your music sources. This is where Koito shines: it supports multiple sources simultaneously. Connect your Spotify, your local music player, your Plex server—all feeding into the same database. The synchronization is surprisingly robust, handling conflicts gracefully when the same track appears from multiple sources.
Pro tip: Set up a reverse proxy (I use Nginx Proxy Manager) with SSL. Since you'll be accessing this from mobile apps, you want that HTTPS connection. The mobile apps actually handle token-based authentication quite well once you've got the secure connection configured.
Beyond Basic Scrobbling: The Analytics Powerhouse
Here's where Koito starts to pull ahead of commercial alternatives. Once you've collected a few weeks of data, the analytics dashboard becomes genuinely useful. We're not talking about simple "top artists this week" displays. Koito offers temporal analysis (how your listening changes throughout the day, week, or seasons), genre evolution tracking, and even mood-based categorization if you connect your Last.fm tags.
I've been testing this for about a month, and I've discovered patterns I never noticed. For instance, I listen to significantly more instrumental music on weekday afternoons (probably while working) and more vocal-heavy genres in the evenings. That's the kind of insight that can actually inform how you organize your music libraries or create playlists.
The API is another killer feature. It's RESTful, well-documented, and—crucially—doesn't have arbitrary rate limits. Want to build a custom visualization of your listening history? Pull the data into Python with Pandas and create exactly what you want. Interested in training a simple ML model to predict what you'll want to hear next? The data's there, in your control. This openness enables experimentation that's impossible with closed platforms.
Privacy and Data Ownership: The Core Philosophy
Let's address the elephant in the room. When you use a service like Last.fm, you're trading your listening data for their service. That data gets aggregated, analyzed, and potentially sold or used for advertising. Even if you trust the company today, acquisitions happen. Policies change. The value of decades-long listening histories for training recommendation algorithms is only increasing.
Koito's approach is fundamentally different. Your data never leaves your server. The synchronization with music sources happens directly between your instance and the service (like Spotify's API), with your personal API keys. There's no middleman collecting metadata about your collection.
This has practical implications beyond just privacy. Your data retention policy is whatever you want it to be. Keep everything forever? Fine. Automatically delete plays older than five years? Also fine. Create complex rules about what gets stored (maybe you don't care about tracking background music but want detailed data about focused listening sessions)? You can build that.
The community raised excellent questions about data minimization in the original discussion. Koito's developer has implemented sensible defaults—it doesn't store your Spotify credentials, only OAuth tokens with limited permissions—but ultimately gives you control. That's the self-hosted ethos in action.
Integration Ecosystem: Playing Well with Others
No tool exists in a vacuum, especially in the self-hosted world. Koito's strength here is its growing list of integrations. The Plex support is solid, though it requires the Plex Pass for webhook functionality. For Jellyfin users, there's a community plugin in development. Local music players like MusicBee and foobar2000 work through existing scrobbler plugins that can be pointed to your Koito instance instead of Last.fm.
But the most interesting integrations are with other self-hosted tools. Want to display your currently playing track on your personal website? There's an embeddable widget. Interested in creating automated playlists based on your listening patterns? You could connect Koito's API to something like Funkwhale or Airsonic-Advanced.
I've even seen community members experimenting with Home Assistant integrations—imagine your lights changing color based on the genre of music you're playing, or your smart thermostat adjusting based on whether you're having a high-energy workout session or a chill jazz evening. These might sound like edge cases, but they demonstrate the platform's flexibility.
Common Pitfalls and Troubleshooting
Even with the improvements in v0.1.3, you might hit some snags. Based on community reports and my own testing, here are the most common issues and how to fix them.
First, mobile app synchronization can be flaky if your server's clock isn't synchronized with NTP. This causes token expiration issues that manifest as mysterious "authentication failed" messages. The fix is simple: ensure your Docker host has proper time synchronization.
Second, the initial music source connections sometimes time out if you have aggressive firewall rules. The Spotify OAuth flow in particular needs to redirect back to your instance. If you're behind a reverse proxy, make sure you've configured the X-Forwarded headers correctly.
Third, database growth. PostgreSQL is efficient, but if you're tracking multiple users with decades of listening history (imported from Last.fm), the database can grow larger than expected. The documentation now includes pruning strategies, but I'd recommend setting up regular backups from day one. A simple cron job dumping the database weekly has saved me from accidental data loss more than once.
Finally, remember that this is still version 0.1.3. There will be bugs. The community Discord is active, and the developer is responsive, but have realistic expectations. Take regular backups before major updates.
The Future of Self-Hosted Music Analytics
Where does Koito go from here? The roadmap discussed in the community includes some exciting features. Collaborative filtering between instances (with explicit opt-in) could create a federated recommendation system without centralized data collection. Better radio/automix generation using your personal listening patterns is in development. There's even talk of integrating with physical scrobblers for vinyl playback.
But more broadly, Koito represents a shift in how we think about our digital footprints. Music listening is deeply personal—it scores our lives, marks our memories, reflects our moods. Should that intimate data be a commodity for platforms, or should it be a personal archive we control and learn from?
As streaming services continue to consolidate and algorithms become more opaque, tools like Koito offer an alternative path. They acknowledge that yes, we want the insights and convenience of tracking, but we want it on our terms. The technology has finally caught up to that desire.
Conclusion: Is Koito Right for You?
So should you switch from Last.fm to Koito? It depends. If you're comfortable with basic Docker administration and value data ownership, absolutely. The setup is no harder than most self-hosted tools, and the payoff is genuine ownership of your musical identity.
If you're deeply invested in Last.fm's social features or rely on their recommendations, the transition might be rougher. Koito is primarily a personal analytics tool, not a social network. But you can run both in parallel—scrobble to both services while you evaluate.
What I appreciate most about Koito is its philosophy. It treats your listening history as valuable personal data worth protecting and understanding. In a world where our digital traces are constantly harvested, that perspective feels increasingly important. Version 0.1.3 proves this isn't just a theoretical ideal—it's a working, practical tool that gets better with each release.
The installation instructions are on GitHub. The community is welcoming. Your music data is waiting to be reclaimed. What are you listening to today?
