Canada's Food Guide MCP Server

from pydantic import BaseModel, Field from typing import List, Dict # Simple math tool input class SimpleMathInput(BaseModel): """Input model for simple mathematical calculations with variables""" expression: str = Field(..., description="Mathematical expression with variables (e.g., '2 * x + 3 * y - 10')") variables: Dict[str, float] = Field(..., description="Dictionary of variable names and their values (e.g., {'x': 5, 'y': 2})") class ServingSizeInput(BaseModel): """Input model for serving size calculations""" session_id: str = Field(..., description="Session identifier containing the recipe") recipe_id: str = Field(..., description="Recipe ID to scale") target_servings: int = Field(..., description="Desired number of servings", gt=0) class IngredientScaleInput(BaseModel): """Input model for scaling individual ingredients""" session_id: str = Field(..., description="Session identifier containing the recipe") recipe_id: str = Field(..., description="Recipe ID containing the ingredient") ingredient_name: str = Field(..., description="Name of ingredient to scale") scale_factor: float = Field(..., description="Multiplication factor (e.g., 2.0 for double, 0.5 for half)", gt=0) class BulkIngredientScaleInput(BaseModel): """Input model for scaling multiple ingredients at once""" session_id: str = Field(..., description="Session identifier containing the recipe") recipe_id: str = Field(..., description="Recipe ID containing the ingredients") ingredient_scales: Dict[str, float] = Field(..., description="Map of ingredient names to scale factors") class RecipeComparisonInput(BaseModel): """Input model for comparing recipes by servings or ingredients""" session_id: str = Field(..., description="Session identifier containing the recipes") recipe_ids: List[str] = Field(..., description="List of recipe IDs to compare", min_items=2) comparison_type: str = Field("servings", description="Type of comparison: 'servings', 'ingredients', or 'portions'") # Bulk math calculation models class BulkMathCalculation(BaseModel): """Individual calculation within a bulk math operation""" id: str = Field(..., description="Unique identifier for this calculation (e.g., 'honey_cals', 'protein_total')") expression: str = Field(..., description="Mathematical expression with variables (e.g., 'base_calories * conversion_factor')") variables: Dict[str, float] = Field(..., description="Dictionary of variable names and their values for this expression") class BulkMathInput(BaseModel): """Input model for bulk mathematical calculations""" calculations: List[BulkMathCalculation] = Field(..., description="List of calculations to perform in one operation", min_items=1) # Note: DRI and nutrient analysis functionality is now implemented # through dedicated modules in src.db.dri_tools and src.db.cnf_tools