AutoEQ MCP Server

pip install autoeq-mcp

An MCP (Model Context Protocol) server that gives AI assistants access to the AutoEQ headphone equalization database — 8,800+ headphones and IEMs with parametric EQ settings, sound signature analysis, and Harman preference scores.

한국어 README

What It Does

Ask your AI assistant things like:

• "Get me the EQ settings for the HD650"
• "Compare the HE400se and HD600"
• "Recommend warm-sounding over-ear headphones"
• "What are the top-ranked IEMs by Harman score?"

The server automatically analyzes frequency response measurements across 8 bands and classifies each headphone's sound signature (Neutral, Warm, Bright, Dark, V-shaped, etc.).

Demo

Headphone comparison with vocal suitability analysis

Finding similar IEMs by sound signature

Tools

Tool	Description
eq_search	Search by name, type (over-ear/in-ear/earbud), sound signature, or measurement source
eq_profile	Get full EQ profile — parametric EQ, fixed band EQ, per-band analysis with visual bars
eq_compare	Side-by-side comparison of two headphones across all frequency bands
eq_recommend	Recommendations by preference (neutral, warm, bright, bass, vocal, fun, analytical)
eq_ranking	Harman headphone listener preference score rankings
eq_targets	List all 61 available target curves (Harman, Diffuse Field, etc.)
eq_sync	Pull latest data from AutoEQ GitHub and rebuild the database

Example Output

# Sennheiser HD 650
- Source: oratory1990
- Type: over-ear
- Harman preference score: 84.0
- Sound signature: Neutral, Harman-like

## Per-band analysis (deviation from target, dB)
  Sub-bass (20-60Hz):   -3.2 dB [·······▓▓▓|··········] sub-bass lacking
  Bass (60-250Hz):      +0.8 dB [··········|··········] close to target
  Mid (500-1kHz):       -0.3 dB [··········|··········] close to target
  Presence (2k-4kHz):   +1.4 dB [··········|▓·········] detail emphasis
  Air (8k-20kHz):       -2.1 dB [········▓▓|··········] closed / lacking air

## Parametric EQ (Preamp: -6.5 dB)
  #  Type        Fc (Hz)      Q  Gain (dB)
  1  LowShelf        105   0.70       +6.5
  2  Peaking        1800   1.20       -2.3
  ...

Installation

Claude Code / Claude Desktop (stdio)

# Install
pip install autoeq-mcp

# Initial database sync (clones AutoEQ repo + builds SQLite DB, ~20s)
autoeq-mcp --sync

# Add to Claude Code
claude mcp add autoeq_mcp -- autoeq-mcp

For Claude Desktop, add to your config file:

{
  "mcpServers": {
    "autoeq": {
      "command": "autoeq-mcp"
    }
  }
}

SSE Mode (Remote / Multi-client)

# Start SSE server
AUTOEQ_MCP_PORT=3008 autoeq-mcp --sse

# With allowed hosts for DNS rebinding protection
AUTOEQ_MCP_ALLOWED_HOSTS="your-domain.com,localhost" autoeq-mcp --sse

From Source

git clone https://github.com/verIdyia/autoeq-mcp
cd autoeq-mcp
pip install -e .
autoeq-mcp --sync

Configuration

All configuration is via environment variables:

Variable	Default	Description
AUTOEQ_DATA_DIR	~/.autoeq-mcp	Directory for repo clone and SQLite DB
AUTOEQ_MCP_PORT	3008	SSE server port
AUTOEQ_MCP_HOST	0.0.0.0	SSE server host
AUTOEQ_MCP_ALLOWED_HOSTS	(none)	Comma-separated allowed hosts for SSE

Data Source

All headphone data comes from AutoEQ by Jaakko Pasanen (MIT License).

• 8,800+ headphone/IEM profiles
• 22 measurement sources (oratory1990, crinacle, Rtings, and more)
• 61 target curves (Harman 2018/2019, Diffuse Field, etc.)
• 2,300+ Harman preference scores

The database syncs from the AutoEQ GitHub repository. Run eq_sync or autoeq-mcp --sync to update.

How Sound Signatures Work

The server analyzes each headphone's frequency response error (deviation from target) across 8 bands and classifies it:

Signature	Characteristics
Neutral	All bands within ±2 dB of target
Warm	Elevated bass, flat/recessed treble
Bright	Elevated treble, flat/recessed bass
Dark	Recessed treble
V-shaped	Elevated bass + treble, recessed mids
U-shaped	Elevated bass + treble
Bass-heavy	Strongly elevated bass (>3 dB)
Mid-forward	Elevated mids, flat bass/treble
Harman-like	Total deviation < 1.5 dB average

License

MIT — See LICENSE