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c0dr

Canteen MCP

by c0dr
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

食堂 MCP

模型上下文协议 (MCP) 服务器可通过简单的 API 集成访问食堂的午餐菜单。

描述

Canteen MCP 是一个基于 FastMCP 的服务器，它提供了一个用于检索食堂每日午餐菜单的工具。它连接到菜单 API，并提供一个结构化的接口来查询特定日期的菜单数据。

Related MCP server: Strapi MCP Server

特征

  • 获取任何特定日期的午餐菜单

  • 基于httpStream的实时通信传输

  • 基于环境的配置

  • 具有输入验证的类型安全 API

安装

npm install

配置

复制示例环境文件并使用您的值更新它：

cp .env.example .env

环境变量

多变的

描述

例子

API_URL

午餐菜单 API 的 URL

https://lunch-menu-ai.vercel.app/api/v1/menu

港口

MCP 服务器的端口

8080

端点

HTTP 端点

/端点

用法

启动服务器：

npm start

可用工具

获取午餐菜单

检索特定日期的午餐菜单。

  • 参数：

    • date ：YYYY-MM-DD 格式的字符串

  • 返回：包含菜单数据的 JSON 字符串

  • 例子：

    const result = await tool.execute({ date: "2024-10-05" });

发展

先决条件

  • Node.js >= 18

  • npm

以开发模式运行

npm run dev

Docker

构建图像

docker build -t canteen-mcp .

运行容器

docker run -d \
  -p 8080:3000 \
  -e API_URL=your_api_url \
  -e PORT=3000 \
  -e ENDPOINT=/http \
  --name canteen-mcp \
  canteen-mcp

使用 GitHub 容器注册表

拉取最新镜像：

docker pull ghcr.io/[your-username]/canteen-mcp:latest

部署

部署到 Hetzner

  1. 通过 SSH 进入你的 Hetzner 服务器：

ssh root@your-server-ip

  1. 如果尚未安装，请安装 Docker：

curl -fsSL https://get.docker.com | sh

  1. 创建 docker-compose.yml 文件：

version: '3.8'
services:
  canteen-mcp:
    image: ghcr.io/c0dr/canteen-mcp:latest
    restart: always
    ports:
      - "8080:3000"
    environment:
      - API_URL=your_api_url
      - PORT=3000
      - ENDPOINT=/http

  1. 启动服务：

docker-compose up -d

执照

该项目根据 MIT 许可证获得许可 - 有关详细信息，请参阅 LICENSE 文件。

基于https://github.com/punkpeye/fastmcp-boilerplate

Available Tools

1 tool
get_lunch_menuA
Read-only

Get the lunch menu from the canteen for a specific date

ParametersJSON Schema
NameRequiredDescriptionDefault
dateYesThe date to get the menu for (YYYY-MM-DD)

TDQS

A3.6/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already provide readOnlyHint=true and openWorldHint=true, indicating this is a safe read operation with open-world assumptions. The description adds context about retrieving a menu for a date but does not disclose additional behavioral traits like error handling, data freshness, or format details. No contradiction with annotations is present.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that efficiently conveys the tool's purpose without any wasted words. It is appropriately sized and front-loaded, making it easy to understand quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (one parameter, read-only, no output schema), the description is reasonably complete. It covers the main action and parameter intent, though it could benefit from mentioning the return format or potential limitations. With annotations handling safety and world assumptions, the description is adequate but not exhaustive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with the parameter 'date' fully documented in the schema (including description, pattern, and type). The description mentions 'for a specific date' but adds no extra meaning beyond what the schema provides, so it meets the baseline of 3 for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('lunch menu from the canteen'), including the scope ('for a specific date'). It distinguishes what the tool does effectively, though there are no sibling tools to differentiate from, which prevents a perfect score of 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage by specifying 'for a specific date', suggesting when to use it (when you need a menu for a particular date). However, it lacks explicit guidance on when not to use it or alternatives, and there are no sibling tools mentioned, so no comparison is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev1.0.0
    • First observedget_lunch_menu
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A3.5/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The tool 'get_lunch_menu' has a clear and distinct purpose that cannot be confused with any other tool in this set.

Naming Consistency5/5

Since there is only one tool, it inherently follows a consistent naming pattern. The tool name 'get_lunch_menu' uses a verb_noun structure, which is clear and predictable, though no comparison with other tools is possible.

Tool Count2/5

A single tool is too few for a server named 'Canteen MCP', which suggests a broader scope related to canteen operations. This minimal set severely limits functionality, as it only allows retrieving the lunch menu without any other operations like ordering, payment, or menu management.

Completeness1/5

The tool set is severely incomplete for a canteen domain. It only provides a 'get' operation for the lunch menu, with no coverage for creating, updating, or deleting menu items, handling orders, payments, or other typical canteen workflows, leading to significant gaps that will cause agent failures.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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