USDA api

curl -sSL https://raw.githubusercontent.com/yourusername/usda-api-mcp/main/install.sh | bash

- Search Foods- Find any food with detailed nutrition facts
- Nutrition Analysis- Complete nutrient breakdowns
- Brand Information- Ingredients, categories, manufacturers
- Bulk Lookups- Multiple foods at once
- Research Data- USDA's gold-standard food database

- "What's the nutrition info for salmon?"
- "Compare chicken breast vs tofu protein"
- "Find high-fiber breakfast foods"
- "Show vitamin content of spinach"

# Clone the repository git clone https://github.com/yourusername/usda-api-mcp.git cd usda-api-mcp # Install dependencies uv sync # Set up environment echo "USDA_API_KEY=your_key_here" > .env # Run the MCP server uv run main.py

usda-api-mcp/ ├── main.py # MCP server implementation ├── gui_installer.py # Web-based GUI installer ├── install.sh # Command-line installer ├── pyproject.toml # Dependencies ├── create_app.sh # Build Mac app bundle └── dist/ # Distribution files

- search_foods(query, page_size, page_number)- Search food database
- get_food_details(fdc_id, nutrients)- Get detailed food information
- get_multiple_foods(fdc_ids, nutrients)- Bulk food lookup
- list_foods(data_type, page_size, page_number)- Browse foods
- get_food_nutrients(fdc_ids, nutrients)- Get specific nutrients

# Build Mac app bundle ./create_app.sh # Create distribution zip cd dist && zip -r "USDA-Food-Tools-Installer.zip" "USDA Food Tools Installer.app" # Test the app open "USDA Food Tools Installer.app"

The server integrates with USDA FoodData Central API v2:

- Base URL:https://api.nal.usda.gov/fdc/v2/
- Authentication: API key in query parameters
- Rate Limits: 3600 requests/hour (free tier)
- Data Types: Foundation, SR Legacy, Survey, Branded foods
- Fork the repository
- Create a feature branch:git checkout -b feature-name
- Make your changes and test thoroughly
- Submit a pull request

# Test MCP server directly uv run main.py # Test GUI installer python3 gui_installer.py # Test command-line installer ./install.sh

The project uses a simple Mac app bundle approach:

- No complex packaging (py2app issues resolved)
- Shell script launcher with embedded Python
- Self-contained with port conflict resolution
- Automatic cleanup of existing processes

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