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Autoeq Mcp

Autoeq Mcp

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github.com/verIdyiaGames & Entertainment6Updated 32w ago

About Autoeq Mcp

Autoeq Mcp gives AI assistants access to the AutoEQ headphone equalization database. It is for people looking up EQ profiles, comparing headphones, or finding models by sound preference, with tools for frequency analysis, rankings, recommendations, and data sync.

Key features

  1. 01Search headphones by name and type
  2. 02Retrieve parametric and fixed-band EQ
  3. 03Compare frequency bands across two headphones
  4. 04Recommend headphones by preference
  5. 05View Harman preference score rankings
  6. 06Sync AutoEQ data

Use cases

  1. 01Find EQ settings for a specific headphone
  2. 02Compare headphone frequency response and sound
  3. 03Filter headphones by sound preference
  4. 04Review Harman score rankings

MCP support

The MCP server exposes AutoEQ database tools for AI assistants, including search, EQ profile lookup, comparison, recommendations, rankings, and data sync. It supports stdio and SSE modes.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project 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

ToolDescription
eq_searchSearch by name, type (over-ear/in-ear/earbud), sound signature, or measurement source
eq_profileGet full EQ profile — parametric EQ, fixed band EQ, per-band analysis with visual bars
eq_compareSide-by-side comparison of two headphones across all frequency bands
eq_recommendRecommendations by preference (neutral, warm, bright, bass, vocal, fun, analytical)
eq_rankingHarman headphone listener preference score rankings
eq_targetsList all 61 available target curves (Harman, Diffuse Field, etc.)
eq_syncPull 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:

VariableDefaultDescription
AUTOEQ_DATA_DIR~/.autoeq-mcpDirectory for repo clone and SQLite DB
AUTOEQ_MCP_PORT3008SSE server port
AUTOEQ_MCP_HOST0.0.0.0SSE 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:

SignatureCharacteristics
NeutralAll bands within ±2 dB of target
WarmElevated bass, flat/recessed treble
BrightElevated treble, flat/recessed bass
DarkRecessed treble
V-shapedElevated bass + treble, recessed mids
U-shapedElevated bass + treble
Bass-heavyStrongly elevated bass (>3 dB)
Mid-forwardElevated mids, flat bass/treble
Harman-likeTotal deviation < 1.5 dB average

License

MIT — See LICENSE

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