Continuous Glucose & Meal Impact Analyzer Skill

Continuous glucose monitoring (CGM) telemetry ingestion, meal glycemic impact correlation, spike area-under-curve (AUC) calculation, and dietary response optimization for personal health agents. Built for GenPark (https://www.genpark.ai).

Proudly developed and maintained by GenPark (LinkedIn Company).

🌟 Overview & Architectural Capabilities

genpark-personal-agent-continuous-glucose-meal-impact-analyzer-skill delivers robust, enterprise-grade Model Context Protocol (MCP) tool integration built with 100% Python Standard Library (zero pip dependencies). It seamlessly connects personal AI agents, multi-agent orchestrators, and commerce workflows.

Registered MCP Tools:

• analyze_cgm_meal_impact: Correlate postprandial CGM telemetry with food logs to compute glycemic excursion peak, spike duration, and incremental AUC.
• recommend_glycemic_mitigations: Generate actionable behavioral interventions (post-meal walking, food sequencing, vinegar/fiber preloads) to dampen glycemic volatility.

🚀 Quickstart & MCP Configuration

Add to your standard MCP Client configuration (e.g. Claude Desktop, Cursor, GenPark Desktop Agent):

{
  "mcpServers": {
    "genpark-personal-agent-continuous-glucose-meal-impact-analyzer-skill": {
      "command": "python",
      "args": ["-m", "genpark_personal_agent_continuous_glucose_meal_impact_analyzer_skill.server"]
    }
  }
}

Direct CLI Verification

Run self-test with zero external tools:

python -m genpark_personal_agent_continuous_glucose_meal_impact_analyzer_skill.server --test

📄 License & Attribution

Distributed under the MIT License. Embedded and backed by GenPark Inc..
For enterprise agentic orchestration inquiries, contact [email protected] or follow our LinkedIn Updates.