Menus Recommender

Name: Menus Recommender
Author: spyyps

by spyypsversion 1.0.1i★ –iRuns on your computer

Registry nameio.github.spyyps/menus-recommender

Install

Overview

Description from the maker (original English)

全球美食加权随机推荐：基于 396 道菜的知识库，给出多样化的就餐推荐。

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "menus-recommender": {
      "command": "uvx",
      "args": [
        "menus-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add menus-recommender -- uvx menus-mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "menus-recommender": {
      "command": "uvx",
      "args": [
        "menus-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "menus-recommender": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "menus-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account spyyps, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

More stars than 0% of the other 32691 servers in this category
Published to the registry more recently than 12% of the other 32691 servers in this category
Basic checks equal to or better than 100% of the other 32691 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Menus Recommender safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.1) reached the registry 5 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Dialyne

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Spec Driven Development

by formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Runs on your computer★ 440MITUpdated 14 months ago

Install

Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated 2 days ago

Install

Dialyne

by dialyne

Real phone calls in France for AI agents: dial +33 numbers, menus, hold, AI disclosure.

Runs in the cloudUpdated today

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

menus-mcp：全球美食推荐 MCP Server

基于 462 道菜、41 个菜系的全球美食知识库做加权随机推荐。任何支持 Model Context Protocol（MCP）的 AI agent 均可使用，包括：

Claude Desktop
Cline
Cursor
Continue
其他 MCP 兼容客户端

快速安装

也可在 MCP Registry 直接搜到本 server（io.github.spyyps/menus-recommender）。

方式 1：uvx（推荐，无需安装）

"mcpServers": { "menus": { "command": "uvx", "args": ["menus-mcp"] } } }

uvx 会自动从 PyPI 下载并运行，首次启动稍有延迟（数据加载约 1s），后续缓存到本地。

方式 2：pip install

pip install menus-mcp

然后在 MCP 客户端配置中：

"mcpServers": { "menus": { "command": "menus-mcp" } } }

方式 3：本地源码运行

git clone https://github.com/spyyps/recommend-dish

cd recommend-dish pip install -r mcp-server/requirements.txt

运行入口

python3 mcp-server/server.py

或在 mcp-server/ 目录下：

cd mcp-server && python3 -m menus_mcp

然后客户端配置：

"mcpServers": { "menus": { "command": "python3", "args": ["/path/to/recommend-dish/mcp-server/server.py"] } } }

开放的工具

`recommend_dishes`

主推荐工具。参数（皆为可选）：

参数	类型	默认	说明
`count`	int	3	推荐数量
`keywords`	str	""	逗号分隔的关键词（OR语义），见下方白名单
`price_tier`	str	""	经济(≤20)/实惠(21-50)/中档(51-100)/高档(101-200)/奢华(>200)
`max_price`	int	0	价格上限（CNY）
`cuisine`	str	""	菜系名（如「川菜」「日本料理」）
`geo`	str	""	地理大类（如「亚洲」「欧洲」）
`exclude_ids`	str	""	逗号分隔的菜品 ID，用于换一批去重
`seed`	int	0	随机种子（0=系统时间）

支持的关键词白名单：

口味：麻辣、辣、甜、酸、咸、鲜
食材：海鲜、牛肉、羊肉、猪肉、鸡肉、素食
类型：面食、米饭类、汤、甜品、烧烤、火锅、咖喱、汉堡披萨、饮品

否定注意：用户说「不要太辣」时不要传入 辣——传空即可。关键词做硬过滤，传入就会强制匹配。

返回示例（JSON）：

"dishes": [ {"id": "cn_ch_001", "name": "麻婆豆腐", "name_en": "Mapo Tofu", "price": 38, "cuisine": "川菜", "region": "中华料理", "description": "嫩豆腐配牛肉末，以花椒和豆瓣酱炒制，麻辣鲜香"} ], "exhausted": false, "filters": {"count": 3, "keywords": ["辣"], "price_tier": "", "relaxed": false, ...}, "candidate_pool_size": 54, "returned": 3 }

exhausted=true 表示候选池不足，应触发兜底链（放宽约束、网络搜索、LLM 常识）。

`list_keywords`

返回支持的关键词白名单。无参数。

兜底推荐

MCP server 仅负责第一层（本地知识库 + 加权随机）。当 exhausted=true 时，应自行按以下链兜底：

降级过滤：去掉价格约束，重试
Web 搜索：查 "{用户原话} 推荐菜品"
LLM 常识：基于通用知识推荐，标注「非知识库菜品」

算法说明

关键词硬过滤：用户传关键词时菜品必须至少匹配一个（OR）
反偏置：权重 × 1/√(该菜系菜品数)，防止大菜系压制小菜系
多样性：同一菜系最多 ceil(count/3) 道
价格松弛：候选不足时自动去价格档重试一次

发布

cd mcp-server

pip install build python3 -m build twine upload dist/*

详见 PyPI 发布指南。

Menus Recommender

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

Dialyne

README from the maker

menus-mcp：全球美食推荐 MCP Server

快速安装

方式 1：uvx（推荐，无需安装）

方式 2：pip install

方式 3：本地源码运行

运行入口

或在 mcp-server/ 目录下：

开放的工具

recommend_dishes

list_keywords

兜底推荐

算法说明

发布

`recommend_dishes`

`list_keywords`