Audio Analyzer
Gives Claude direct audio analysis capabilities through seven MCP tools that run spectral, harmonic, rhythm, and stereo field analysis on local audio files. Point it at an mp3 or wav and get back key detection, tempo, LUFS loudness, frequency band energy, stereo width, MFCC timbre coefficients, and structural section boundaries. The full_analysis tool returns a complete profile in under 2 seconds for a 60 second track, all pure Rust with no Python or FFmpeg dependencies. Includes an A/B compare tool for mix revisions. Ships as a single binary with one click Claude Desktop install via mcpb bundles. Useful for music production feedback, audio forensics, or any workflow where you need Claude to reason about sound characteristics beyond what vision models can infer from spectrograms.
- GitHub stars
- 27
- tools
- 6
- transport
- STDIO
- last updated
- Mar 13, 2026
Tools
6 toolsPublic tool metadata for what this MCP can expose to an agent.
audio_infoBasic file info: duration, sample rate, sample count
Basic file info: duration, sample rate, sample count
No parameter schema in public metadata yet.
spectral_featuresBrightness, richness, loudness, texture, timbre (MFCCs), frequency band energy, spectral contrast, dynamic range, LUFS loudness, stereo field
Brightness, richness, loudness, texture, timbre (MFCCs), frequency band energy, spectral contrast, dynamic range, LUFS loudness, stereo field
No parameter schema in public metadata yet.
harmonic_analysisKey detection, pitch class distribution, tonnetz
Key detection, pitch class distribution, tonnetz
No parameter schema in public metadata yet.
rhythm_analysisTempo (BPM), beat positions, tempo stability
Tempo (BPM), beat positions, tempo stability
No parameter schema in public metadata yet.
full_analysisEverything above in one call, plus percussive character (HPSS), stereo field, and section boundaries.
Everything above in one call, plus percussive character (HPSS), stereo field, and section boundaries.
No parameter schema in public metadata yet.
compareA/B two tracks -- analyses both and returns a compact diff table
A/B two tracks -- analyses both and returns a compact diff table
No parameter schema in public metadata yet.
Sponsors
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audio_visualizer_rs
An MCP server that gives Claude the ability to hear music.
Point Claude at any audio file and it can tell you the key, tempo, dynamics, timbre, percussive character, stereo field, structural sections, and how the music evolves over time -- all from raw audio analysis, no images, no guessing, under 1% context window usage.
Compare two tracks side-by-side. Detect where the music changes structurally — intro, verse, chorus, bridge — and zoom into the moments that matter.
What is this?
LLMs can see (vision) and read (text), but they can't hear. This project bridges that gap by running real audio analysis -- the same DSP techniques used in music information retrieval research -- and returning structured numerical data that Claude can reason about.
It's an MCP server that exposes audio analysis as tools Claude can call on demand. Ask Claude to analyze a song and it will decode the audio, run spectral/harmonic/rhythm/percussive analysis, and return the results as compact text. No spectrograms, no images, no wasted tokens.
Details
- Repository
- github.com/juzzydee/audio-analyzer-rs
- Category
- Media & Entertainment
- Package
https://github.com/JuzzyDee/audio-analyzer-rs/releases/download/v1.0.0/audio-analyzer-darwin-arm64.mcpb- Transport
- STDIO
- Registry
- MCP registry, active
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