Personal MCP Server

Personal MCP Server

A Model Context Protocol server for personal health and well-being tracking. This server provides tools and resources for tracking workouts, nutrition, and daily journal entries, with AI-assisted analysis through Claude integration.

Features

Workout Tracking

  • Log exercises, sets, and reps
  • Track perceived effort and post-workout feelings
  • Calculate safe training weights with rehabilitation considerations
  • Historical workout analysis
  • Shoulder rehabilitation support
  • RPE-based load management

Nutrition Management

  • Log meals and individual food items
  • Track protein and calorie intake
  • Monitor hunger and satisfaction levels
  • Daily nutrition targets and progress
  • Pre/post workout nutrition tracking
  • Meal timing analysis

Journal System

  • Daily entries with mood and energy tracking
  • Sleep quality and stress level monitoring
  • Tag-based organization
  • Trend analysis and insights
  • Correlation analysis between workouts, nutrition, and well-being
  • Pattern recognition in mood and energy levels

Installation

Installing via Smithery

To install Personal Health Tracker for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install personal-mcp --client claude

Prerequisites

  • Python 3.10 or higher
  • pip or uv package manager

Using pip

pip install -e .

Development Installation

git clone https://github.com/yourusername/personal-mcp.git cd personal-mcp uv pip install -e ".[dev]"

Usage

Basic Server

Run the server with default settings:

personal-mcp run

Development Mode

Run with hot reloading for development:

personal-mcp dev

MCP Inspector

Debug with the MCP Inspector:

personal-mcp inspect

Claude Desktop Integration

Install to Claude Desktop:

personal-mcp install --claude-desktop

Configuration Options

personal-mcp --help

Available options:

  • --name: Set server name (default: "Personal Assistant")
  • --db-path: Specify database location
  • --dev: Enable development mode
  • --inspect: Run with MCP Inspector
  • -v, --verbose: Enable verbose logging

MCP Tools

Workout Tools

# Log a workout workout = { "date": "2024-01-07", "exercises": [ { "name": "Bench Press", "sets": [ {"weight": 135, "reps": 10, "rpe": 7} ] } ], "perceived_effort": 8 } # Calculate training weights params = { "exercise": "Bench Press", "base_weight": 200, "days_since_surgery": 90, "recent_pain_level": 2, "recent_rpe": 7 }

Nutrition Tools

# Log a meal meal = { "meal_type": "lunch", "foods": [ { "name": "Chicken Breast", "amount": 200, "unit": "g", "protein": 46, "calories": 330 } ], "hunger_level": 7, "satisfaction_level": 8 } # Check nutrition targets targets = await mcp.call_tool("check_nutrition_targets", {"date": "2024-01-07"})

Journal Tools

# Create a journal entry entry = { "entry_type": "daily", "content": "Great workout today...", "mood": 8, "energy": 7, "sleep_quality": 8, "stress_level": 3, "tags": ["workout", "recovery"] } # Analyze entries analysis = await mcp.call_tool("analyze_journal_entries", { "start_date": "2024-01-01", "end_date": "2024-01-07" })

Development

Running Tests

# Run all tests pytest # Run with coverage pytest --cov=personal_mcp # Run specific test file pytest tests/test_database.py

Code Quality

# Format code black src/personal_mcp # Lint code ruff check src/personal_mcp # Type checking mypy src/personal_mcp

Project Structure

personal-mcp/ ├── src/ │ └── personal_mcp/ │ ├── tools/ │ │ ├── workout.py │ │ ├── nutrition.py │ │ └── journal.py │ ├── database.py │ ├── models.py │ ├── resources.py │ ├── prompts.py │ └── server.py ├── tests/ │ ├── test_database.py │ ├── test_server.py │ └── test_cli.py ├── pyproject.toml └── mcp.json

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Commit your changes
  4. Push to the branch
  5. Create a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

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security - not tested
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license - not found
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quality - not tested

A Model Context Protocol server for tracking personal health and well-being, offering tools for workout logging, nutrition management, and daily journaling with AI-assisted analysis integration.

  1. Features
    1. Workout Tracking
      1. Nutrition Management
        1. Journal System
        2. Installation
          1. Installing via Smithery
            1. Prerequisites
              1. Using pip
                1. Development Installation
                2. Usage
                  1. Basic Server
                    1. Development Mode
                      1. MCP Inspector
                        1. Claude Desktop Integration
                          1. Configuration Options
                          2. MCP Tools
                            1. Workout Tools
                              1. Nutrition Tools
                                1. Journal Tools
                                2. Development
                                  1. Running Tests
                                    1. Code Quality
                                    2. Project Structure
                                      1. Contributing
                                        1. License