suggestRecipes

Instructions

Implementation Reference

• src/tools/index.ts:151-170 (handler)

  The actual tool handler for 'suggestRecipes' - accepts nameOrBarcode, looks up the product, and calls createRecipeSuggestionRequest + requestSampling to generate AI recipes.

  server.registerTool('suggestRecipes', {
    description: 'Get AI recipe suggestions using a product',
    inputSchema: productSchema
  }, async ({ nameOrBarcode }) => {
    if (!nameOrBarcode?.trim()) {
      return { content: [{ type: 'text' as const, text: 'Provide a product.' }], isError: true };
    }
  
    const productData = await findProduct(nameOrBarcode);
    if (!productData?.product) {
      return { content: [{ type: 'text' as const, text: `"${nameOrBarcode}" not found.` }], isError: true };
    }
  
    try {
      const res = await requestSampling(server, createRecipeSuggestionRequest(productData.product));
      return { content: [{ type: 'text' as const, text: `# Recipes using ${productData.product.product_name}\n\n${getResponseText(res)}` }] };
    } catch (e: any) {
      return { content: [{ type: 'text' as const, text: `Recipe generation failed: ${e.message}` }], isError: true };
    }
  });

• src/tools/index.ts:50-50 (schema)

  Input schema for suggestRecipes: { nameOrBarcode: z.string() }

  const productSchema = { nameOrBarcode: z.string() };

• src/tools/index.ts:151-170 (registration)

  Registration of 'suggestRecipes' tool via server.registerTool with description and inputSchema.

  server.registerTool('suggestRecipes', {
    description: 'Get AI recipe suggestions using a product',
    inputSchema: productSchema
  }, async ({ nameOrBarcode }) => {
    if (!nameOrBarcode?.trim()) {
      return { content: [{ type: 'text' as const, text: 'Provide a product.' }], isError: true };
    }
  
    const productData = await findProduct(nameOrBarcode);
    if (!productData?.product) {
      return { content: [{ type: 'text' as const, text: `"${nameOrBarcode}" not found.` }], isError: true };
    }
  
    try {
      const res = await requestSampling(server, createRecipeSuggestionRequest(productData.product));
      return { content: [{ type: 'text' as const, text: `# Recipes using ${productData.product.product_name}\n\n${getResponseText(res)}` }] };
    } catch (e: any) {
      return { content: [{ type: 'text' as const, text: `Recipe generation failed: ${e.message}` }], isError: true };
    }
  });

• src/sampling/sampling-service.ts:90-134 (helper)

  createRecipeSuggestionRequest builds a SamplingRequest with system prompt for generating 4 recipe types (low-calorie, protein-rich, quick & easy, family-friendly) using product data.

  export function createRecipeSuggestionRequest(productData: any): SamplingRequest {
    const productName = productData.product_name || "this product";
    const category = productData.categories || "food item";
    const ingredients = productData.ingredients_text || "";
    const nutriments = productData.nutriments || {};
    const allergens = productData.allergens || "";
    const brands = productData.brands || "";
  
    return {
      messages: [
        {
          role: "user",
          content: {
            type: "text",
            text: `Generate recipe suggestions for ${productName} (${brands}). ` +
              `Nutritional profile: Energy ${nutriments.energy_100g || "unknown"} kcal, ` +
              `Fat ${nutriments.fat_100g || "unknown"}g, ` +
              `Proteins ${nutriments.proteins_100g || "unknown"}g, ` +
              `Carbs ${nutriments.carbohydrates_100g || "unknown"}g.\n\n` +
              `Category: ${category}\nIngredients: ${ingredients}\nAllergens: ${allergens}`
          }
        }
      ],
      modelPreferences: {
        hints: [{ name: "claude-3" }, { name: "gpt-4o" }],
        intelligencePriority: 0.8,
        speedPriority: 0.5
      },
      systemPrompt: `You are a creative culinary nutritionist. Generate 4 recipe suggestions:
  1. LOW-CALORIE: Light meal focusing on weight management
  2. PROTEIN-RICH: Recipe for fitness enthusiasts  
  3. QUICK & EASY: Minimal prep and cooking time
  4. FAMILY-FRIENDLY: Balanced meal for all ages
  
  For each recipe, provide:
  - Recipe name
  - Ingredient list with measurements
  - Brief preparation steps
  - Approximate nutrition per serving
  - Health benefit highlight`,
      includeContext: "thisServer",
      temperature: 0.7,
      maxTokens: 3500
    };
  }

• src/sampling/sampling-service.ts:51-75 (helper)

  requestSampling sends the sampling/createMessage request to the LLM client via MCP protocol, used by the suggestRecipes handler.

  export async function requestSampling(
    mcpServer: McpServer,
    request: SamplingRequest
  ): Promise<CreateMessageResult> {
    try {
      const response = await mcpServer.server.request({
        method: "sampling/createMessage",
        params: {
          messages: request.messages,
          modelPreferences: request.modelPreferences,
          systemPrompt: request.systemPrompt,
          includeContext: request.includeContext,
          temperature: request.temperature,
          maxTokens: request.maxTokens,
          stopSequences: request.stopSequences,
          metadata: request.metadata
        }
      }, CreateMessageResultSchema);
  
      return response as CreateMessageResult;
    } catch (error: unknown) {
      const errorMessage = error instanceof Error ? error.message : String(error);
      throw new Error(`Sampling request failed: ${errorMessage}`);
    }
  }