yeqv111/mccarbon
麦麦碳账本 · 基于麦当劳 MCP 的个人餐饮碳足迹估算与减排模拟器 | Personal dining carbon footprint estimator powered by McDonald's MCP
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README & documentation
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省钱不是主题，热量不是主题，点餐更不是主题——麦麦碳账本要讲的是「你的麦当劳一年，排了多少碳，以及怎么少排一点」。 它用麦当劳官方 MCP 拉取你的历史订单，按三层碳核算模型（餐品 / 包装 / 配送）估算出个人餐饮碳足迹，产出一份单文件 HTML「碳账本」：总碳足迹、碳等级 A–E、三层结构、月度曲线、碳重集中类别、最碳重一单、直观换算（几棵树 / 开车多少公里），以及一个减排模拟器。 为什么选这个方向？ 全站参赛作品里，没有任何一份做环保 / 碳足迹维度（基于对官方仓库全部 529 份参赛作品的竞品分析，详见 workbuddy.md）。它天然契合麦当劳自身的「Plan for Change / 2050 净零」叙事，同时是一个真正的个人工具——不是玩梗，是能用的东西。 嫌 PYTHONPATH=src 麻烦的话，装一次就能用短命令： 环境要求：Python 3.9+（已在 3.9.6 与 3.13.12 实测通过），零第三方依赖。 碳足迹题材最怕被质疑「数字是编的」，所以这里把口径写在明处。三层模型： 中文菜单的绝大多数餐品没有公开实测值，因此按碳类别中值外推（牛肉 2.40 / 鸡肉 1.00 / 鱼 0.80 / 植物基 0.30 / 小食 0.35 … kg CO2e 每份）。这比把英国单品数据硬套到中文菜单上更稳，也更好解释。 依据《中国产品全生命周期温室气体排放系数库》： 按渠道分摊：外送（餐盒 + 餐具 + 袋）远重于到店 / 自提。 参考国内外卖研究：每单平均 111.80 g CO2e，其中包装占 86%，配送段本身仅约 15.6 g（电动两轮为主）。…
Read the full README ↗ · Preview checked 2026-10-29T21:33:21.328Z
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What this repository does
麦麦碳账本 · 基于麦当劳 MCP 的个人餐饮碳足迹估算与减排模拟器 | Personal dining carbon footprint estimator powered by McDonald's MCP
Repository facts
- Owner
- yeqv111
- Primary language
- Python
- Stars
- 1,933
- Forks
- 43
- Open issues + pull requests
- 0
- License
- MIT
- Archived
- No
- Default branch
- main
- Created
- 2026-10-12T09:45:08.000Z
- Last push
- 2026-10-13T07:15:56.000Z
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