Audio Analysis, Plugin Knowledge, MIDI Learning
Real audio processing capabilities for ChatGPT and AI assistants.
Audio Analysis Core
- analyze_audio - Deep audio analysis (50+ features, librosa-powered)
- classify_genre - AI genre classification with confidence scoring
- assess_quality - Professional quality assessment for mixing/mastering
- suggest_mixing - AI-driven mixing recommendations
Professional Visualizations
- export_visualization - Waveforms, spectrograms, spectral analysis
- 7 chart types - Including genre and quality analysis charts
- 4 formats - PNG, SVG, WebP, JPEG (300 DPI)
- 4 color schemes - Professional visualization themes
MIDI Controller Intelligence
- learn_midi_mapping - Smart MIDI controller learning
- list_midi_devices - Real MIDI device enumeration
- Intelligent mapping - Context-aware MIDI CC assignments
- Real device detection - Automatic hardware identification
Device Optimization Engine
- optimize_device - Smart optimization for 7 device types
- 7 device types - Audio interfaces, headphones, studio monitors, controllers
- 4 contexts - Recording, mixing, live performance, critical listening
- Performance gains - Real latency and quality improvements
Plugin Scanner Pro
- list_plugins - Scan system plugins (VST3, VST2, AU, AAX, LV2)
- 13 categories - Reverb, Delay, Modulation, Dynamics, EQ, Distortion
- Smart detection - Cross-platform plugin format support
- Manufacturer ID - Automatic brand recognition
Real-time Performance
- Sub-50ms latency - Lightning-fast audio processing
- Multiple formats - WAV, MP3, FLAC, M4A, OGG support
- Real libraries - Built with librosa, numpy, mido, scipy
- Production ready - No mocks, no stubs, real functionality
🛠️ Complete Tool Reference
All 10 professional tools in the Audio Agent MCP Server
analyze_audio
Deep audio analysis with 50+ features using librosa
export_visualization
🆕 Professional audio visualization export
classify_genre
AI-powered music genre classification
assess_quality
Professional audio quality assessment
suggest_mixing
AI-driven mixing recommendations
learn_midi_mapping
Intelligent MIDI controller learning
list_midi_devices
Real MIDI device enumeration
optimize_device
Smart optimization for 7 device types
list_plugins
Plugin scanner with 13 categories
test_plugin_quality
🆕 AI-powered plugin testing and quality analysis
🎨 Visualization Gallery
Professional audio visualizations generated with export_visualization tool
Waveform Visualization
Classic waveform display with amplitude analysis
Spectrogram Analysis
Frequency analysis with time-frequency representation
Spectral Centroid
Brightness and frequency center analysis over time
Technical Details: All visualizations generated using real audio analysis with librosa, matplotlib at 300 DPI export quality
Example Outputs
Audio Analysis Results
{
"file": "jazz_piano.wav",
"duration": 3.45,
"sample_rate": 44100,
"tempo": 128.5,
"key": "C major",
"mode": "major",
"time_signature": "4/4",
"loudness": {
"integrated": -12.3,
"range": 8.7
},
"spectral_features": {
"centroid": 2147.3,
"bandwidth": 1876.2,
"rolloff": 3891.5
},
"mfcc": [13 coefficients],
"chroma": [12 pitch classes],
"tonnetz": [6 harmonic features]
}
AI-Powered Insights
{
"genre_classification": {
"genre": "jazz",
"confidence": 0.87,
"subgenres": ["smooth_jazz", "contemporary"]
},
"instrument_detection": {
"piano": 0.92,
"upright_bass": 0.78,
"brush_drums": 0.65
},
"mixing_analysis": {
"dynamics": "well_balanced",
"frequency_balance": "warm",
"stereo_width": "natural",
"clarity_score": 8.2
},
"suggestions": [
"Consider subtle compression",
"Add 2kHz presence for vocal clarity",
"Monitor low-end buildup below 80Hz"
]
}