How I Built a Tool to Discover New Music

When I lived in Missoula, Montana I loved tuning into the local college radio station KBGA. It was wonderful hearing high quality, curated music from artists I had never heard of.

When I moved away from Missoula, I missed discovering new music through KBGA. I could listen to their web stream online, but this had limitations:

  • To listen to a certain show, I had to remember to tune in at a specific time. I often forgot, or could not tune in because it was during an inconvenient time.

  • I started heavily using Spotify. I took pride in maintaining an especially heady "Favorites" playlist. There was no easy way for me to hear a song on KBGA and quickly add it to this playlist.

kind.fm was built to address these issues, and create a place where wonderfully curated playlists arranged by the best independent radio dj's can be shared with the world.

How It Works: Gluing Four Services Together

I was able to build a solution by combining four different services.

I noticed that KBGA DJs logged text of their playlists into a site called Spinitron. I was able to connect to their API in order to grab the text of the playlists that I cared about.

I was then able to connect to Spotify in order to automatically create streamable playlists from the the Spinitron data.

To add some visual flavor, I was able to connect to musicbrainz, and then fanart.tv to find a high quality image for one of the artists featured in each playlist.

I then turned to my favorite programming language & framework, database, and UI toolkit to present these playlists online.

The Result

The result of all this a product in which I solved my own needs. I am able to instantly listen to highly curated playlists from my favorite independent radio DJ's, and easily add my favorite songs to my Spotify playlist.

I've used this system myself for the past year, and found some of my favorite songs through it. After months of tweaking and finalizing the app, I am happy to now release it to you. I can only hope that my work might help you get that incredibly special feeling of discovering an amazing song for the first time.

Enjoy.

Listen to kind.fm