一个用于与 Tandoor Recipe 管理器交互的模型上下文协议(MCP)服务器.

□ 当前状态

-==YTET -伊甸园字幕组=- 翻译: 成功实施和测试

• 创建 tandoor meal plan:成功实施并测试
• **get recipes:成功实施和测试
• 额,额,额,额… 成功实施和测试
• \\\\\\\ n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ 已执行
• **get meal 类型:已执行
• ** 获得 关键词**:已执行
• 已执行 -===YTET -伊甸园字幕组=- 翻译: 已执行 -=============================================================================================================================================================================================================================================================== 已执行
• **add shopping list 项目:已执行(附有名称查询)
• ** 更新 购物 列表 项目**:已执行
• ** ** 移动 购物 列表 项目**:已执行

□ 特性

• 在Tandoor制作配料和说明书
• 在具体日期和膳食种类的膳食计划中添加食谱
• 利用各种标准(名称、关键词、食物、评分)寻找食谱
• 收回按日期和膳食种类过滤的膳食计划
• 获取具体食谱的全部细节
• 列出现有餐饮类型、关键词、食品和单位
• 管理购物列表项目(视图、添加、更新、去除)

□ 设置

1. 安装依赖性:

Tandoor MCP Server

A Model Context Protocol (MCP) server for interacting with Tandoor Recipe Manager.

Current Status

• ✅ create_tandoor_recipe: Successfully implemented and tested
• ✅ create_tandoor_meal_plan: Successfully implemented and tested
• ✅ get_recipes: Successfully implemented and tested
• ✅ get_meal_plans: Successfully implemented and tested
• ✅ get_recipe_details: Implemented
• ✅ get_meal_types: Implemented
• ✅ get_keywords: Implemented
• ✅ get_foods: Implemented
• ✅ get_units: Implemented
• ✅ get_shopping_list: Implemented
• ✅ add_shopping_list_item: Implemented (with name lookup)
• ✅ update_shopping_list_item: Implemented
• ✅ remove_shopping_list_item: Implemented

Features

• Create recipes in Tandoor with ingredients and instructions
• Add recipes to meal plans for specific dates and meal types
• Search for recipes using various criteria (name, keywords, foods, rating)
• Retrieve meal plans filtered by date range and meal type
• Retrieve full details for a specific recipe
• List available meal types, keywords, foods, and units
• Manage shopping list items (view, add, update, remove)

Setup

1. Install dependencies:

   npm install
   

2. Build the server:

   npm run build
   

3. Run the server manually (for testing):

   # Windows PowerShell
   $env:TANDOOR_URL = "https://your-tandoor-instance.com"
   $env:TANDOOR_API_TOKEN = "your-api-token"
   node .\build\index.js
   
   # Windows CMD
   set TANDOOR_URL=https://your-tandoor-instance.com
   set TANDOOR_API_TOKEN=your-api-token
   node .\build\index.js
   
   # Linux/macOS
   TANDOOR_URL=https://your-tandoor-instance.com TANDOOR_API_TOKEN=your-api-token node ./build/index.js
   

4. Configure in MCP settings:

   {
     "mcpServers": {
       "tandoor": {
         "command": "node",
         "args": ["path/to/tandoor-mcp-server/build/index.js"],
         "env": {
           "TANDOOR_URL": "https://your-tandoor-instance.com",
           "TANDOOR_API_TOKEN": "your-api-token"
         },
         "disabled": false,
         "autoApprove": []
       }
     }
   }
   

5. If you want everything autoApprove…

      "autoApprove": [
        "add_shopping_list_item",
        "create_tandoor_meal_plan",
        "create_tandoor_recipe",
        "get_foods",
        "get_keywords",
        "get_meal_plans",
        "get_meal_types",
        "get_recipe_details",
        "get_recipes",
        "get_recipes",
        "get_shopping_list",
        "get_units",
        "remove_shopping_list_item",
        "update_shopping_list_item"
      ]

6. Add ./.clinerules to your project directory

• optionally also add ./memory-bank with a markdown or text file list of foods you like or dislike in case you’d like suggestions for meals from the assistant.