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.
A zero-dependency, mathematically rigorous personal agent skill that evaluates central aortic pulse wave reflections, arterial wall elasticity, and late-systolic cardiac afterload via applanation tonometry pulse wave analysis.
flowchart TD
A[Radial/Carotid Applanation Tonometry] --> B[Generalized Transfer Function / PWA Waveform]
B --> C[Identify Forward Peak P1 & Late Systolic Peak P2]
C --> D[Compute Augmentation Pressure AP = P2 - P1 & AIx]
D --> E[Normalize to Heart Rate 75 bpm AIx@75 & Measure Tr]
E --> F[Vascular Aging & Subendocardial Perfusion Index SEVR]Related MCP server: cutaneous-microcirculation
from client import CentralAorticAugmentationIndexClient
client = CentralAorticAugmentationIndexClient()
result = client.evaluate_pwa(
aortic_systolic_bp_mmhg=115.0,
aortic_diastolic_bp_mmhg=75.0,
inflection_pressure_mmhg=105.0,
reflection_time_tr_ms=140.0,
heart_rate_bpm=72.0
)
print("Augmentation Index AIx@75 (%):", result["wave_reflection_kinetics"]["aix_normalized_at_75bpm_pct"])
print("SEVR (%):", result["myocardial_perfusion"]["subendocardial_viability_ratio_sevr_pct"])
print("Stiffness Class:", result["vascular_stiffness_assessment"]["stiffness_classification"])Apache-2.0
This server cannot be deployed
Body composition for AI: BMI, body fat, FFMI, waist-to-height, plus saved measurement trends.
Fuses biometric signals into a stress score (0-100) for AI adaptation. MCP + A2A native.
Read-only Apple Health data synced from your iPhone: sleep, heart rate, HRV, workouts and trends.
Cardiopulmonary exercise test (CPET) analysis: ventilatory thresholds, metrics and substrate use.
