jprbom/-health-dashboard-mcp
If you are the rightful owner of -health-dashboard-mcp and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.
The Health Dashboard MCP Server is a robust Model Context Protocol server designed to enable AI assistants to interact with personal health and biometric data, offering intelligent insights and recommendations.
Health Dashboard MCP Server
A powerful MCP (Model Context Protocol) server that enables AI assistants like Claude to interact with personal health and biometric data, providing intelligent insights and recommendations.
Features
- Biometric Recording: Track weight, blood pressure, heart rate, sleep, steps, glucose, and temperature
- Health Summaries: Get comprehensive health metric summaries for any time period
- Trend Analysis: AI-powered analysis of health trends with actionable insights
- Goal Setting: Set and track health goals with progress monitoring
- Smart Recommendations: Receive personalized health recommendations based on your data
- Wearable Integration: Support for Fitbit, Apple Watch, and Garmin devices (coming soon)
Installation
- Clone this repository:
git clone https://github.com/[your-username]/health-dashboard-mcp.git
cd health-dashboard-mcp
- Install dependencies:
npm install
- Create a
.env
file for your API keys (optional, for wearable integrations):
FITBIT_CLIENT_ID=your_fitbit_client_id
FITBIT_CLIENT_SECRET=your_fitbit_client_secret
# Add other API keys as needed
Configuration
For Claude Desktop
Add to your Claude Desktop configuration file:
Windows: %APPDATA%\Claude\claude_desktop_config.json
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
{
"mcpServers": {
"health-dashboard": {
"command": "node",
"args": ["C:/path/to/health-dashboard-mcp/src/index.js"]
}
}
}
Usage
Once configured, you can interact with your health data through Claude:
Recording Biometrics
- "Record my weight as 150 lbs"
- "Log my blood pressure: 120/80"
- "I slept for 7.5 hours last night, quality was good"
Viewing Summaries
- "Show me my health summary for the last week"
- "What were my average steps this month?"
- "Display my blood pressure trends"
Getting Insights
- "Analyze my weight trend over the last 30 days"
- "Are there any concerning patterns in my health data?"
- "How has my sleep quality affected my heart rate?"
Setting Goals
- "Set a goal to lose 10 pounds by March"
- "I want to average 10,000 steps per day"
- "Help me improve my sleep quality"
Available Tools
- record_biometrics: Record various health metrics
- get_health_summary: Retrieve health data summaries
- analyze_trends: Analyze health metric trends
- set_health_goals: Set and track health goals
- get_recommendations: Get AI-powered health recommendations
- generate_health_report: Generate comprehensive health reports
- ai_health_coach: Interactive health coaching based on your data
- predict_health_outcomes: Predict future health metrics based on trends
Privacy & Security
- All health data is stored locally on your machine
- No data is sent to external servers (except for optional wearable syncing)
- Sensitive information is excluded from git commits via
.gitignore
- You maintain full control over your health data
Development
Project Structure
health-dashboard-mcp/
āāā src/
ā āāā index.js # Main server file
ā āāā tools/ # Individual tool implementations
ā āāā integrations/ # Wearable device integrations
ā āāā utils/ # Utility functions
āāā health_data/ # Local health data storage (gitignored)
āāā .env # Environment variables (gitignored)
āāā .gitignore # Git ignore file
āāā package.json # Project dependencies
āāā README.md # This file
Contributing
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature
) - Commit your changes (
git commit -m 'Add amazing feature'
) - Push to the branch (
git push origin feature/amazing-feature
) - Open a Pull Request
Roadmap
- Full wearable device integration (Fitbit, Apple Watch, Garmin)
- Advanced visualization capabilities
- Export to common health data formats
- Integration with health apps and services
- Machine learning models for health predictions
- Medication tracking and reminders
- Nutrition tracking integration
License
This project is licensed under the MIT License - see the LICENSE file for details.
Disclaimer
This tool is for personal health tracking and insights only. It is not a substitute for professional medical advice, diagnosis, or treatment. Always consult with qualified healthcare providers for medical concerns.
Support
For issues, questions, or suggestions, please open an issue on GitHub. "# -health-dashboard-mcp"