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worryzyy

基于Anduin2017 / HowToCook (程序员在家做饭指南)的mcp server

Publisherworryzyy
RepositoryHowToCook-mcp
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Stars
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  • Connect tools to AI workflows

    HowToCook exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    773 stars and 59 forks from the linked repository.

🍳 HowToCook-MCP Server 🥘 -- 炫一周好饭,拒绝拼好饭

English | 简体中文

本项目 CDN 加速及安全防护由 Tencent EdgeOne 赞助

亚洲最佳 CDN、边缘和安全解决方案 - Tencent EdgeOne

让 AI 助手变身私人大厨,为你的一日三餐出谋划策!

基于Anduin2017/HowToCook打造的 MCP(Model Context Protocol)服务器,让 AI 助手能够为你推荐菜谱、规划膳食,解决"今天吃什么"的世纪难题!

数据来源:Anduin2017/HowToCook ⭐ 没有 star 的同学快去点个星星吧!

🎉 想直接使用当前 MCP?立即体验 https://howtocookmcp.weilei.site/

🎉 同时,我们也提供了 DXT(Desktop Extensions)供大家体验,一键安装到 Claude Desktop

如下:请确保你已经安装了最新版的 Claude Desktop, 当前 MCP 的 DXT 文件已上传代码库,可以自行下载或者 Fork 本仓库自行构建

DXT DXT DXT

本地开发如何打包成 DXT?

1.运行 npm install -g @anthropic-ai/dxt

2.在包含本地 MCP 服务器的文件夹中,运行 dxt init。也就是您 MCP 的根目录,此命令将引导您创建manifest.json

3.运行dxt pack创建 dxt 文件

现在,任何支持 DXT 的应用都可以运行您的本地 MCP 服务器。例如,使用适用于 macOS 和 Windows 的 Claude 打开该文件即可显示安装对话框

具体参阅:anthropics/dxt

📸 效果预览

功能预览1 功能预览2

🔌 支持的 MCP 客户端

本服务器适用于所有支持 MCP 协议的 AI 助手和客户端,包括但不限于:

  • 🤖 Claude 桌面应用
  • 📝 Cursor
  • 💼 其他支持 MCP 的客户端

✨ 美味功能

该 MCP 服务器提供以下美食工具:

  1. 📚 查询全部菜谱 - 获取所有可用菜谱数据,做菜百科全书 -- 慎用这个--上下文太大
  2. 🔍 根据分类查询菜谱 - 按照分类筛选菜谱,想吃水产?早餐?荤菜?主食?一键搞定!
  3. 📖 查询指定菜谱 - 根据菜谱名称查询特定菜谱的完整详情,包括食材、步骤等
  4. 🧩 智能推荐膳食 - 根据你的忌口、过敏原和用餐人数,为你规划整整一周的美味佳肴
  5. 🎲 不知道吃什么 - 选择困难症福音!根据人数直接推荐今日菜单,再也不用纠结了

🚀 快速上手

📋 先决条件

  • Node.js 16.0.0+ 🟢
  • npm 或 yarn 📦

💻 安装步骤

  1. 克隆美食仓库
bash
git clone https://github.com/worryzyy/howtocook-mcp.git
cd howtocook-mcp
  1. 安装依赖(就像准备食材一样简单!)
bash
npm install
  1. 编译代码(烹饪过程...)
bash
npm run build

🎯 命令行参数

服务器支持以下命令行参数:

  • --transport <stdio|http|sse> - 选择传输方式(默认为 stdio)
  • --port <number> - 使用 http 或 sse 传输时的监听端口(默认为 3000)

示例:使用 http 传输并监听 8080 端口

bash
node build/index.js --transport http --port 8080

🍽️ 开始使用

🔥 启动服务器

bash
npm start

🔧 配置 MCP 客户端

推荐使用 Cursor 快速体验(两种方式)

  1. 使用 npm 包:请先运行 npm i -g howtocook-mcp ,否则会出现 Failed to create client

然后在 Cursor 设置中添加 MCP 服务器配置:

json
{
	"mcpServers": {
		"howtocook-mcp": {
			"command": "npx",
			"args": ["-y", "howtocook-mcp"]
		}
	}
}
  1. 如果是克隆仓库本地运行,请使用如下配置
json
{
	"mcpServers": {
		"howtocook-mcp": {
			"command": "node",
			"args": ["youpath\\howtocook-mcp\\build\\index.js"]
		}
	}
}

其他 MCP 客户端

对于其他支持 MCP 协议的客户端,请参考各自的文档进行配置,通常需要指定:

  • 服务器名称: howtocook-mcp
  • 命令: npx -y howtocook-mcp
  1. 重启客户端,让美食魔法生效 ✨

🧙‍♂️ 菜单魔法使用指南

以下是在各种 MCP 客户端中使用的示例提示语:

1. 📚 查询全部菜谱

无需参数,直接召唤美食全书!

请使用howtocook的MCP服务查询所有菜谱

2. 🔍 根据分类查询菜谱

请使用howtocook的MCP服务查询水产类的菜谱

参数:

  • category: 菜谱分类(水产、早餐、荤菜、主食等)

3. 🧩 智能推荐一周菜谱

请使用howtocook的MCP服务为3人推荐一周菜谱,我们家不吃香菜,对虾过敏

参数:

  • allergies: 过敏原列表,如 ["大蒜", "虾"]
  • avoidItems: 忌口食材,如 ["葱", "姜"]
  • peopleCount: 用餐人数 (1-10)

4. 🎲 今天吃什么?

请使用howtocook的MCP服务为4人晚餐推荐菜单

参数:

  • peopleCount: 用餐人数 (1-10)

📝 小贴士

  • 该包已发布至 npm,可直接通过npm install -g howtocook-mcp全局安装
  • 本服务兼容所有支持 MCP 协议的 AI 助手和应用
  • 首次使用时,AI 可能需要一点时间来熟悉如何使用这些工具(就像烧热锅一样)

🤝 贡献

欢迎 Fork 和 Pull Request,让我们一起完善这个美食助手!

📄 许可

MIT License - 随意使用,就像分享美食配方一样慷慨!


🍴 美食即将开始,胃口准备好了吗?

Use HowToCook MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once HowToCook is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add HowToCook as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the HowToCook MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "howtocook-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "<mcp-server-package>"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the HowToCook MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the HowToCook MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use HowToCook to help me with this task?
HowToCook
Sure. I read it.
Here is what I found using HowToCook.

Frequently asked questions

What is the HowToCook MCP server used for?

HowToCook is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use HowToCook MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use HowToCook with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use HowToCook MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With HowToCook connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect HowToCook MCP to TypingMind?

HowToCook runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does HowToCook MCP provide in TypingMind?

HowToCook exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use HowToCook MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If HowToCook requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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