Provides tools and actions for use within the Hermes Personal Agent environment, allowing autonomous agents and LLMs to integrate psychoacoustic modeling results and BMLD calculations for advanced decision-making.
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
Zero-dependency sovereign personal agent skill for non-invasive psychoacoustic modeling of Binaural Masking Level Difference (BMLD), brainstem auditory squelch, and cocktail party speech-in-noise intelligibility.
flowchart TD
Dichotic["Dichotic Hearing Test (S0N0 vs SpiN0)"] --> Phase["Interaural Phase Difference (IPD) Extraction"]
Phase --> BMLD_Calc["BMLD dB Decibel Advantage Engine"]
BMLD_Calc --> Brainstem["Brainstem Processing & Speech Intelligibility Scoring"]
Brainstem --> Agent["OpenClaw / Hermes Personal Agent Actions"]Deterministic Math: Pure Python standard library implementation with zero external dependencies.
Audiological Standard Formulas: Implements clinically validated homophasic and antiphasic decibel differential modeling.
Cocktail Party Intelligibility Modeling: Direct calculation of speech perception advantage in background noise.
Model Context Protocol (MCP): Native JSON-RPC tool integration for LLMs and autonomous agents.
Related MCP server: Personal Agent Focus Recovery Binaural Beats Skill
from client import BinauralMaskingLevelDifferenceClient
client = BinauralMaskingLevelDifferenceClient()
result = client.evaluate_bmld(
s0_n0_threshold_db=64.0,
spi_n0_threshold_db=50.0,
test_frequency_hz=500.0
)
print("BMLD:", result["bmld_db"], "dB")
print("Brainstem Score:", result["brainstem_processing_score"])
print("Classification:", result["classification"])Apache-2.0
This server cannot be deployed
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