Integrates with Apple Health to retrieve fitness metrics, activity data, and weight measurements for health tracking
Provides persistent storage for user meal logging and nutrition tracking data through Google Sheets integration
Uses GPT-4o Vision to process food photos and text descriptions for automatic meal identification and logging
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Healthy Pokeslog my lunch: chicken salad sandwich and apple"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Healthy Pokes
A calorie tracking MCP (Model Context Protocol) server that integrates meal logging with nutrition data and health metrics.
Features
šø Process food photos and text descriptions using GPT-4o Vision
š„ Automatic nutrition estimation via OpenNutrition MCP
š Google Sheets integration for personalized tracking
š Apple Health integration for activity and weight data
š± SMS interface via Poke platform
Architecture
This MCP server acts as a bridge between multiple services:
OpenAI GPT-4o: Extracts food items from photos/text
OpenNutrition MCP: Provides nutrition data
Google Sheets: Stores user data persistently
Apple Health MCP: Retrieves fitness metrics
Poke Platform: Handles messaging interface
Setup
Prerequisites
Python 3.9+
Google Cloud Project with Sheets & Drive APIs enabled
OpenAI API key
Poke API key
Installation
# Clone the repository
git clone https://github.com/mattattacks/healthy-pokes.git
cd healthy-pokes
# Create virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
# Set up environment variables
cp .env.example .env
# Edit .env with your API keysEnvironment Variables
Create a .env file with:
OPENAI_API_KEY=your_openai_key
POKE_API_KEY=your_poke_key
GOOGLE_SERVICE_ACCOUNT_JSON={"type":"service_account"...}
HEALTH_DATA_DIR=/path/to/health/exports # OptionalUsage
Running Locally
python server.pyThe MCP server will be available at http://localhost:8000/mcp
Deploying to Render
This project includes a render.yaml for easy deployment to Render.
MCP Tools
connect_user(email)- Set up Google Sheet for useringest_image(image_url)- Process food photoparse_text(text)- Process text descriptionestimate_from_items(items)- Get nutrition datalog_rows(rows)- Save to Google Sheettoday_total()- Calculate daily intakehealth_summary()- Get Apple Health metricssend_message(text)- Reply via Poke
Development
Project Structure
healthy-pokes/
āāā server.py # Main MCP server
āāā tools/ # MCP tool implementations
ā āāā __init__.py
ā āāā google_sheets.py
ā āāā nutrition.py
ā āāā vision.py
ā āāā messaging.py
āāā utils/ # Helper functions
āāā requirements.txt # Python dependencies
āāā render.yaml # Render deployment config
āāā .env.example # Environment templateTesting
pytest tests/Contributing
Pull requests are welcome! Please ensure all tests pass and follow the existing code style.
License
MIT
Acknowledgments
Built for the HackMIT Poke Challenge
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