OpenClaw Shazam Integration: Song Recognition and Music Discovery

You hear a song at a coffee shop, in a podcast intro, or playing in the background during a video call. Instead of pulling out your phone and opening Shazam, you tell your OpenClaw assistant "What song is this?" and it identifies the track, tells you the artist, and adds it to your Spotify playlist — all through voice or chat. This guide covers setting up song recognition in OpenClaw.

Why Add Song Recognition to OpenClaw?

Song recognition is a small but surprisingly useful OpenClaw capability, especially for Mac Mini deployments with a microphone already connected for voice mode. It turns a common everyday friction — "What is this song? Let me find my phone, open Shazam, hold it up..." — into a single voice command.

Beyond simple identification, the integration enables automated music logging (keep a record of every song that plays in your office), playlist curation (automatically build playlists from songs you encounter), and music discovery (OpenClaw can recommend similar artists and tracks based on your recognition history).

For content creators, the integration also helps identify background music in videos for licensing purposes or creative inspiration.

How Do You Set Up ShazamKit on macOS?

On macOS, OpenClaw can use Apple's ShazamKit framework directly. This is the same recognition engine that powers the Shazam app, with access to its catalog of millions of songs.

Enable the Shazam skill in your OpenClaw configuration:

{
  "skills": {
    "shazam": {
      "enabled": true,
      "engine": "shazamkit",
      "microphone_device": "default",
      "listen_duration_seconds": 10,
      "auto_add_to_playlist": true,
      "playlist_service": "spotify"
    }
  }
}

ShazamKit requires macOS 12 (Monterey) or newer. The recognition runs locally for the audio capture phase, then sends an audio fingerprint (not the raw audio) to Apple's servers for matching. Results typically arrive in 2-5 seconds.

Test with a simple command: say "Hey Claw, what song is this?" while music is playing. OpenClaw should respond with the song title, artist, album, and a link to listen on your preferred streaming service.

How Do You Use Alternative APIs on Linux?

For OpenClaw deployments on Linux or Windows (where ShazamKit is not available), use a third-party audio fingerprinting API:

AudD: REST API for song recognition. Accepts audio files or streams. Free tier includes 300 recognitions per month.

{
  "skills": {
    "shazam": {
      "enabled": true,
      "engine": "audd",
      "api_key": "${AUDD_API_KEY}",
      "microphone_device": "default",
      "listen_duration_seconds": 10
    }
  }
}

ACRCloud: Another popular audio recognition API with a free tier. Supports music, TV shows, and custom audio fingerprints.

Both alternatives work identically from the user perspective — you ask OpenClaw to identify a song and get back the same title, artist, and album information.

How Do You Automate Playlist Building?

With both Shazam and a streaming service integration configured, OpenClaw can automatically add every identified song to a designated playlist:

{
  "skills": {
    "shazam": {
      "auto_add_to_playlist": true,
      "playlist_service": "spotify",
      "playlist_name": "OpenClaw Discovered",
      "spotify_client_id": "${SPOTIFY_CLIENT_ID}",
      "spotify_client_secret": "${SPOTIFY_CLIENT_SECRET}"
    }
  }
}

Every time OpenClaw identifies a song, it searches for it on Spotify and adds it to your "OpenClaw Discovered" playlist. Over time, this builds a curated collection of songs you have encountered in daily life — a personal soundtrack generated passively.

You can also ask OpenClaw to create themed playlists: "Create a playlist of the last 10 songs you identified that were in the electronic genre" or "Which songs did you identify this week that I have not heard before?"

How Does Auto-Shazam Mode Work?

Auto-Shazam mode continuously listens for music and identifies songs without manual triggering. This is useful for logging music in environments like offices, retail spaces, or events.

Configure auto-mode with reasonable intervals to avoid excessive API usage:

{
  "skills": {
    "shazam": {
      "auto_mode": {
        "enabled": true,
        "check_interval_seconds": 30,
        "min_confidence": 0.7,
        "quiet_hours": "23:00-07:00",
        "log_to_file": true
      }
    }
  }
}

Auto-mode samples audio every 30 seconds (configurable), checks if music is playing, and if detected, runs recognition. The min_confidence threshold prevents false matches from background noise. Quiet hours disable auto-recognition during sleeping hours to save resources.

All identified songs are logged with timestamps, making it easy to look back and find "that song that was playing during the 3pm meeting on Tuesday."

FAQ

How does Shazam integration work with OpenClaw?

OpenClaw uses ShazamKit (Apple's song recognition framework) or third-party audio fingerprinting APIs to identify songs playing through a microphone. You can trigger recognition via voice command ("What song is this?"), chat message, or set it to automatically identify songs in the background. Results include song title, artist, album, and streaming links.

Does the Shazam integration require a Mac for OpenClaw?

ShazamKit is an Apple framework and works natively on macOS, making Mac Mini the ideal host. For Linux or Windows OpenClaw deployments, you can use alternative audio fingerprinting services like AudD or ACRCloud that provide REST APIs compatible with any platform.

Can OpenClaw automatically add recognized songs to a Spotify playlist?

Yes. With both Shazam and Spotify integrations configured, OpenClaw can identify a song and immediately add it to a designated Spotify playlist. You can also set up an "auto-shazam" mode that continuously identifies songs and logs them, building a playlist of everything that played in your environment.

Is there a cost for using Shazam recognition in OpenClaw?

ShazamKit on macOS is free for personal use with a generous request limit. Third-party alternatives like AudD offer free tiers (typically 300-500 recognitions per month) and paid plans for higher volume. For casual personal use, the free tiers are more than sufficient.

Ready to Add Music Intelligence to Your OpenClaw?

We configure Shazam integration alongside voice mode and streaming service connections as part of managed Mac Mini OpenClaw deployments. Song recognition from day one.

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*Last updated: March 2026. Published by the Remote OpenClaw team at remoteopenclaw.com.*