Enables AI models to analyze audio files through numerical fingerprints, pitch tracking, and visual spectrograms without requiring direct audio playback. It provides tools for comparing audio iterations and detecting patterns using token-efficient analysis operations.
Enables AI agents to analyze local or URL-hosted audio files with TrackTag, returning professional music metadata such as BPM, key, genres, moods, and 35+ fields. Runs locally on your machine, using your TrackTag API key and credit balance for analyses.
Enables LLMs to analyze music (genre, mood, tempo, key), separate audio stems, detect AI-generated music, and measure loudness using IRCAM Amplify's audio processing APIs.
Enables local, private analysis of YouTube URLs and local audio files to extract BPM, key modulations, vocal presence, transient punch, stereo width, and CLAP vibe embeddings, returning structured sonic signatures for AI agents and CLI users.
Enables AI agents to create and edit Strudel music code, render offline WAV audio, and obtain structured hearing reports with waveform, spectrogram, BPM, and onset analysis.
