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Autoeq MCP

MCP server for AutoEQ headphone equalization database — search, compare, and get EQ settings for 8800+ headphones/IEMs

Install / Use

/learn @verIdyia/Autoeq MCP
About this skill

Quality Score

0/100

Supported Platforms

Claude Code
Claude Desktop
Cursor

README

AutoEQ MCP Server

PyPI License: MIT Python 3.10+ Claude Desktop Claude Code claude.ai

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

Comparison demo — HD650 vs DT 990 Pro with per-band chart and vocal recommendation

Finding similar IEMs by sound signature

Similar search demo — finding IEMs with similar tuning using per-band analysis

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

Related Skills

View on GitHub
GitHub Stars3
CategoryDevelopment
Updated5d ago
Forks0

Languages

Python

Security Score

90/100

Audited on Mar 21, 2026

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