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 evaluation of Cutaneous Post-Occlusive Reactive Hyperemia (PORH), Laser Doppler flowmetry, time-to-peak, and endothelial nitric oxide reserve.
flowchart TD
Baseline["Resting Cutaneous Perfusion Flux Baseline (PU_base)"] --> Occlusion["3-Min Suprasystolic Arterial Occlusion Challenge"]
Occlusion --> Deflation["Cuff Release -> Sudden Shear Stress Surge"]
Deflation --> NORelease["Endothelial Nitric Oxide Synthase (eNOS) & Prostacyclin Surge"]
NORelease --> PeakHyperemia["Peak Reactive Hyperemic Perfusion (PU_peak)"]
PeakHyperemia --> PORHMetrics["PORH Ratio (PU_peak/PU_base) & Time-to-Peak (sec)"]
PORHMetrics --> EndothelialScore["Microvascular Endothelial & Vascular Elasticity Score"]
EndothelialScore --> Agent["OpenClaw / Hermes Personal Agent Lifestyle Prescriptions"]Deterministic Math: Pure Python standard library implementation with zero external dependencies.
Vascular Physiology Standards: Implements validated equations for Laser Doppler flux, hyperemic amplification ratio, and time-to-peak kinetics.
Microvascular Endothelial Dysfunction Detection: Early sensitive screening for subclinical vascular stiffening and endothelial decay.
Model Context Protocol (MCP): Native JSON-RPC tool integration for LLMs and autonomous agents.
Related MCP server: cutaneous-microcirculation
from client import CutaneousMicrovascularPORHClient
client = CutaneousMicrovascularPORHClient()
result = client.evaluate_porh(
baseline_flux_pu=14.2,
peak_hyperemic_flux_pu=72.5,
time_to_peak_sec=7.2,
recovery_time_sec=78.0
)
print("PORH Ratio:", result["porh_amplification_ratio"], "x")
print("Endothelial Score:", result["microvascular_endothelial_score"])
print("Classification:", result["classification"])Apache-2.0
This server cannot be deployed
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