A
licenseB
qualityC
maintenanceTurns any AI assistant into a physiological AI running coach by abstracting fitness APIs and exposing 70+ structured analytical MCP tools based on endurance models.
21
MIT
Personal Agent Mitochondrial Biogenesis MET Flux Skill
Officialby alphaparkinc
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.
Personal Agent Mitochondrial Biogenesis MET Flux Skill
Zero-dependency PGC-1alpha transcriptional induction modeler, CaMK vs. AMPK pathway partitioner, and 80/20 polarized mitochondrial density training optimizer.
Architecture
flowchart TD
WorkoutSession[Session Type, Duration, Average HR, Max HR] --> PathwayModeler[Biochemical Pathway Modeler]
PathwayModeler --> CaMKBranch[Low-Intensity Zone 2: CaMK & p38 MAPK Volume Signaling]
PathwayModeler --> AMPKBranch[High-Intensity Sprints: AMPK Acute Depletion Signaling]
CaMKBranch & AMPKBranch --> PGC1aScore[PGC-1a Transcriptional Score & Biogenesis Tier]
WeeklyCardio[Zone 2 Minutes & HIIT Minutes] --> PolarizedOptimizer[80/20 Polarized Training Optimizer]
PolarizedOptimizer --> Prescription[Mitochondrial Volume & Cristae Efficiency Balance]Related MCP server: Trainner AI MCP Server
Quickstart
from client import PersonalAgentMitochondrialBiogenesisMetFlux
agent = PersonalAgentMitochondrialBiogenesisMetFlux()
res = agent.model_pgc1a_transcriptional_stimulus(session_type="zone2_endurance", duration_minutes=50.0)
print(f"PGC-1a Score: {res['pgc1a_transcriptional_score']} | Pathway: {res['biochemical_signaling_cascade']}")This server cannot be deployed
Maintenance
ActivityMaintained
ResponsivenessNo issues
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