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 sovereign personal agent capability for computational respiratory physiology, evaluating Maximal Inspiratory (MIP) and Expiratory (MEP) Pressures in cmH2O, Black & Hyatt models, and diaphragmatic pump strength.
flowchart TD
PatientData["Demographics: Age & Sex"] --> NormativeModel["Black & Hyatt Prediction Equations (MIP_pred & MEP_pred)"]
MIPMEPData["Measured Static Pressures: MIP (cmH2O) & MEP (cmH2O)"] --> RatioEngine["Percentage of Predicted Force: (Measured / Predicted) * 100%"]
NormativeModel --> RatioEngine
RatioEngine --> DMRI["Diaphragmatic Muscle Resilience Index (DMRI: 0 - 100)"]
DMRI --> IMTPlan["OpenClaw / Hermes Inspiratory Muscle Training (50% MIP) Prescriptions"]Related MCP server: ventilatory-efficiency
from client import RespiratoryMuscleStrengthClient
client = RespiratoryMuscleStrengthClient()
# Assess respiratory pressures (32-year-old male)
res = client.evaluate_respiratory_pressures(
measured_mip_cmh2o=132.0,
measured_mep_cmh2o=245.0,
age_years=32.0,
is_female=False
)
print("MIP % Predicted:", res["pct_predicted_mip"], "%")
print("MEP % Predicted:", res["pct_predicted_mep"], "%")
print("Resilience Score:", res["diaphragmatic_resilience_index"], "/ 100")
print("Status:", res["status"])Add to your claude_desktop_config.json or OpenClaw tool registry:
{
"mcpServers": {
"respiratory-muscle-strength": {
"command": "python",
"args": ["/path/to/genpark-personal-agent-respiratory-muscle-strength-mip-mep-skill/mcp_server.py"]
}
}
}MIT License.
This server cannot be deployed
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