sf-beverage-skus

SF coffee, matcha, and chai catalog API: 439 SKUs across 13 merchants, prices in cents.

我该使用它吗

质量与安全性

A
描述质量
100%
模式完整度
84%
命名质量
93%
投毒风险
100%
权限匹配度
100%
协议合规性
100%

基于对工具定义和协议合规性的自动分析。

上下文开销

~308token 数(工具定义)
~650 B典型响应大小
对注意力的影响极小(占 128k 上下文窗口的 0.24%)

这是每次将服务器的工具加载到模型上下文窗口时所消耗的大致 token 数。数值越高,可用于其他任务的注意力就越少。

安装

一键安装

将以下内容添加到你的 `claude_desktop_config.json` 文件中:

{
  "mcpServers": {
    "sf-beverage-skus": {
      "url": "https://sf-beverage-skus.luff.workers.dev/mcp"
    }
  }
}

远程端点

https://sf-beverage-skus.luff.workers.dev/mcpstreamable-http

它能做什么

工具清单

工具(3)

🟢 只读🟡 写入🔴 删除⚪ 未知
🟢search_skus(category, lat, limit, lon, max_miles, ...)

Search SF beverage SKUs by item name, with optional category filter and geo search. Returns sku_id, merchant, distance, size, and price in integer cents.

输入模式

{
  "type": "object",
  "properties": {
    "category": {
      "enum": [
        "coffee",
        "matcha",
        "chai"
      ],
      "type": "string"
    },
    "lat": {
      "type": "number"
    },
    "limit": {
      "default": 20,
      "maximum": 100,
      "type": "integer"
    },
    "lon": {
      "type": "number"
    },
    "max_miles": {
      "type": "number"
    },
    "q": {
      "description": "item name substring, e.g. 'matcha latte'",
      "type": "string"
    },
    "sort": {
      "default": "distance",
      "enum": [
        "price",
        "distance"
      ],
      "type": "string"
    }
  }
}
🟢get_sku(sku_id)

Full detail for one SKU: item, merchant, location, and every option group with choices and price deltas (cents).

输入模式

{
  "type": "object",
  "properties": {
    "sku_id": {
      "description": "e.g. starbucks--matcha-latte--short",
      "type": "string"
    }
  },
  "required": [
    "sku_id"
  ]
}
🟢price_order(option_ids, sku_id)

Compute an order total: total_cents = sku.price_cents + SUM(option.price_delta_cents). Validates option_ids against the SKU; rejects unknown or inapplicable options.

输入模式

{
  "type": "object",
  "properties": {
    "option_ids": {
      "items": {
        "type": "string"
      },
      "type": "array"
    },
    "sku_id": {
      "type": "string"
    }
  },
  "required": [
    "sku_id"
  ]
}

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