mcp-phenoage-clock

199-mcp/mcp-phenoage-clock

3.3

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An MCP server that calculates biological age using the Morgan Levine PhenoAge clock based on blood biomarkers.

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MCP PhenoAge Clock Server

An MCP (Model Context Protocol) server that calculates biological age using the Morgan Levine PhenoAge clock based on blood biomarkers.

Overview

The PhenoAge clock is a biological aging measure developed by Dr. Morgan Levine and colleagues. It uses 9 blood biomarkers plus chronological age to estimate "phenotypic age" - a measure that captures morbidity and mortality risk better than chronological age alone.

Based on: Levine et al. (2018) "An epigenetic biomarker of aging for lifespan and healthspan" Aging (Albany NY). 2018;10(4):573-591

Installation

Via NPX (Recommended)

npx mcp-phenoage-clock

Via NPM

npm install -g mcp-phenoage-clock
mcp-phenoage-clock

From Source

git clone https://github.com/199-biotechnologies/mcp-phenoage-clock.git
cd mcp-phenoage-clock
npm install
npm run build
npm start

Usage with Claude Desktop

Add to your Claude Desktop configuration file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "phenoage-clock": {
      "command": "npx",
      "args": ["mcp-phenoage-clock"]
    }
  }
}

Available Tools

calculate_phenoage

Calculates your biological age using the PhenoAge formula.

Required biomarkers:

  • age: Chronological age (years)
  • albumin: Albumin (g/dL)
  • creatinine: Creatinine (mg/dL)
  • glucose: Glucose (mg/dL) - must be fasting
  • crp: C-reactive protein (mg/L)
  • lymphocytePercent: Lymphocyte percentage (%)
  • meanCellVolume: Mean cell volume/MCV (fL)
  • redCellDistWidth: Red cell distribution width/RDW (%)
  • alkalinePhosphatase: Alkaline phosphatase (U/L)
  • whiteBloodCellCount: White blood cell count (1000 cells/μL)

Returns:

  • PhenoAge (biological age)
  • Age difference (PhenoAge - chronological age)
  • Mortality score
  • Interpretation

get_biomarker_ranges

Returns reference ranges and optimal values for all biomarkers.

Example Usage in Claude

User: Calculate my PhenoAge with these values:
- Age: 45
- Albumin: 4.2 g/dL
- Creatinine: 0.9 mg/dL
- Glucose: 85 mg/dL
- CRP: 0.5 mg/L
- Lymphocyte %: 30
- MCV: 89 fL
- RDW: 12.5%
- Alkaline phosphatase: 65 U/L
- WBC: 6.2

Claude will use the calculate_phenoage tool and return your biological age.

Understanding Your Results

  • PhenoAge < Chronological Age: Your biological age is younger than your actual age, suggesting good health
  • PhenoAge ≈ Chronological Age: Normal aging pattern
  • PhenoAge > Chronological Age: Your biological age is older than your actual age, suggesting accelerated aging

Important Notes

  1. Fasting Glucose: The glucose measurement must be taken after fasting
  2. Units Matter: Ensure your lab results match the required units
  3. Medical Advice: This tool is for informational purposes only. Always consult healthcare providers for medical decisions
  4. Lab Variations: Different labs may use different reference ranges
  5. Formula Limitations: In rare cases with certain biomarker combinations, the mortality score may reach mathematical limits, resulting in clamped calculations. This is a limitation of the formula, not necessarily indicative of health status

Formula Details

The PhenoAge calculation uses the following formula:

xb = -19.907 - 0.0336×albumin + 0.0095×creatinine + 0.1953×glucose 
     + 0.0954×ln(CRP) - 0.0120×lymphocyte% + 0.0268×MCV 
     + 0.3306×RDW + 0.00188×alkaline_phosphatase + 0.0554×WBC + 0.0804×age

mortality_score = 1 - exp(-exp(xb) × (exp(120×γ) - 1) / γ)
where γ = 0.0076927

PhenoAge = 141.50225 + ln(-0.00553 × ln(1 - mortality_score)) / 0.090165

Development

# Install dependencies
npm install

# Build
npm run build

# Run in development
npm run dev

License

MIT

Contributing

Contributions welcome! Please submit PRs to the GitHub repository.

References

  • Levine ME, Lu AT, Quach A, et al. An epigenetic biomarker of aging for lifespan and healthspan. Aging (Albany NY). 2018;10(4):573-591.
  • Original paper supplementary materials: Table S6 contains the full coefficient values