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.
Dynamic Ocular Accommodative Microfluctuations (AMF) Spectral Analyzer. Evaluates crystalline lens focal oscillations, low-frequency component (LFC: <0.6 Hz), and high-frequency component (HFC: 1.0-2.3 Hz) to quantify visual fatigue and ciliary spasm.
flowchart TD
A[Continuous Diopter Time Series] --> B[Hann Windowing & Mean Subtraction]
B --> C[Discrete Fourier Transform PSD]
C --> D[Band Integration: LFC 0.1-0.6 Hz]
C --> E[Band Integration: HFC 1.0-2.3 Hz]
D & E --> F[AMF Ratio Calculation: HFC / LFC]
F --> G[Ciliary Fatigue Index & Ergonomic Classification]Zero PIP Dependencies: Implemented strictly with Python Standard Library (math, json, sys, typing).
Fourier Spectral Decomposition: Hann-windowed discrete power spectrum analysis.
Objective Ergonomics: Identifies ciliary hypertonicity and digital screen visual fatigue before subjective eyestrain symptoms escalate.
Dual Architecture: Supports native Python import and Model Context Protocol (MCP) JSON-RPC 2.0 stdio interface.
Related MCP server: Surface Electromyography (sEMG) RMS Workload Skill
python example_usage.pyApache-2.0
This server cannot be deployed
Structured analysis API and remote MCP tool for text, JSON records and numeric series.
Documentation for the Spektralwerk spectrometer SCPI API as a streamable HTTP MCP Server
Cycle analysis of your own time series: dominant cycles, cycle scans, cyclic RSI and consensus.
Private health and fitness analytics through a secure remote MCP connection.
