Purpose
autoeq-mcp is an MCP (Model Context Protocol) server used to connect the AutoEQ headphone equalization database to AI assistants. It allows AI assistants to directly access parametric EQ settings, sound signature analysis, and Harman preference scores for over 8,800 headphones and IEMs.
Main Capabilities
- Provides equalization data for over 8,800 headphone/IEM configurations.
- Supports searching for headphones by name or sound style.
- Can retrieve parametric EQ settings for a specified headphone.
- Supports band-by-band comparison between two headphones, including vocal suitability analysis.
- Supports finding similar IEMs by sound signature.
- Automatically analyzes frequency response measurement data, covering 8 frequency bands, and classifies each headphone's sound signature as neutral, warm, bright, dark, V-shaped, etc.
- Can view lists of headphones or IEMs ranked by Harman score.
- The data integrates 22 measurement sources (such as oratory1990, crinacle, Rtings, etc.).
- Supports 61 target curves (Harman 2018/2019, Diffuse Field, etc.).
- Includes over 2,300 Harman preference scores.
Usage
This server can be connected to AI assistants, enabling them to answer requests such as:
- "Get the EQ settings for the HD650"
- "Compare the HE400se and HD600"
- "Recommend warm-sounding over-ear headphones"
- "What are the IEMs ranked by Harman score?"
For deployment, the repository provides the following modes:
- stdio mode for Claude Code / Claude Desktop.
- Claude Desktop requires adding the corresponding configuration in the configuration file.
- Supports SSE mode (remote / multi-client).
- All configuration is done through environment variables.
Database synchronization: run eq_sync or autoeq-mcp --sync to update the data from the AutoEQ GitHub repository.
Use Cases
- Headphone enthusiasts or audio engineers querying and comparing equalization settings for different headphones.
- Finding or recommending headphones based on sound signature (such as warm, bright, V-shaped, etc.).
- Filtering headphones or IEMs based on Harman preference scores.
- Performing headphone sound signature comparisons and vocal suitability analysis in AI assistants.
Limitations
- The data comes from the AutoEQ project (Jaakko Pasanen, MIT License).
- Specific installation commands, environment variable names, and complete configuration details are not yet expanded in the provided materials and require reference to the project repository.
- Information regarding fees, pricing, and platform support scope is not yet provided.
