recipe-shoplist-mcp
Turns a natural language meal request into a structured recipe and a categorized shopping list with optional search links for grocery stores.
README
recipe-shoplist-mcp
Turns a meal idea into a categorized shopping list with one-click search links — no accounts, no API keys.
An MCP (Model Context Protocol) server that takes a natural language meal request, generates a structured recipe, consolidates ingredients into a categorized shopping list, and optionally generates pre-filled search URLs for common grocery stores.
Features
- Recipe Generation — Describe what you want ("something quick with chicken and rice", "vegan pasta for 4") and get a structured recipe with ingredients, steps, and timing
- Shopping List Builder — Consolidates duplicate ingredients across multiple recipes (two recipes need garlic? → combined quantity)
- Grocery Category Grouping — Items sorted by store section: produce, dairy, meat, pantry, spices, etc.
- Export Formats — Plain text, Markdown, or clickable search links for Amazon Fresh, Walmart, or generic Google Shopping
- Save to File — Export your shopping list as a
.mdor.txtfile to open, print, or share - Vague Ingredient Flagging — Flags entries like "some spices" so you know to clarify
- Multi-Recipe Merging — Plan a week of meals and get one combined shopping list
Installation
git clone https://github.com/Sara-Eltayeb/recipe-shoplist-mcp.git
cd recipe-shoplist-mcp
npm install
npm run build
Register in Your MCP Client
Add to your MCP client configuration (e.g. Claude Desktop, opencode, etc.):
{
"mcpServers": {
"recipe-shoplist": {
"command": "node",
"args": ["/absolute/path/to/recipe-shoplist-mcp/dist/index.js"]
}
}
}
Or if installed globally via npm:
{
"mcpServers": {
"recipe-shoplist": {
"command": "recipe-shoplist-mcp"
}
}
}
Tools
generate_recipe
Generate a structured recipe from a natural language request.
| Parameter | Type | Description |
|---|---|---|
request |
string | Natural language meal request |
servings |
number? | Number of servings (default: 4) |
dietary_restrictions |
string[]? | e.g. ["vegan", "gluten-free"] |
build_shopping_list
Consolidate ingredients from one or more recipes into a categorized shopping list.
| Parameter | Type | Description |
|---|---|---|
ingredients |
Ingredient[] | Array of {name, quantity, unit} |
recipe_names |
string[]? | Names of source recipes |
export_list
Export the latest shopping list in your preferred format.
| Parameter | Type | Description |
|---|---|---|
format |
"text" | "markdown" | "url_links" |
Output format |
store |
"amazon_fresh" | "walmart" | "generic"? |
Store for URL links |
save_list_to_file
Save the shopping list to a local .md or .txt file.
| Parameter | Type | Description |
|---|---|---|
filename |
string? | Filename without extension |
format |
"text" | "markdown"? |
File format (default: markdown) |
Example Prompts
- "Plan 3 dinners for this week and give me one combined shopping list"
- "Make a shopping list for a vegan pasta night and give me Walmart search links"
- "I want something quick with chicken and rice, then save the list to a file"
- "Give me 2 meal ideas for the week and combine everything into one markdown shopping list"
Limitations
- No cart automation — Search links open a search or product page on the retailer's site. Adding items to a cart and checking out requires retailer partner API access, which is not available without approval.
- No external API keys — Recipe generation relies on the calling AI assistant's own creativity. This server structures and validates the output but does not call external recipe APIs.
- Vague ingredients — Terms like "some spices" or "seasoning to taste" are flagged for clarification rather than guessed at.
License
MIT
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。