MCD w/Work skill
A skill for ordering from McDonald's China via its official MCP: coupon-aware prices, nutrition, order status and a quiet summary.
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Broad access
Why this level
- Creates real McDonald's China orders on behalf of the token owner; nothing is sent without explicit confirmation.
- The token and order data (phone, address, order number) must not be left in public repositories or summary pages.
Install
- Works in
In your terminal, with SkillFoxx CLI
npx skillfoxx add skills/mcd-w-workDetects the agents on your machine, shows the access level and pins the version.
Other ways to install
Access and checks
How we reviewBroad accessThe tool can change data, run commands or handle secrets.
- Creates real McDonald's China orders on behalf of the token owner; nothing is sent without explicit confirmation.
- The token and order data (phone, address, order number) must not be left in public repositories or summary pages.
This is third-party code. Review the repository files before installing.
What it does
MCD w/Work (麦麦在呢, "Mai Mai is here") is a WorkBuddy skill on top of the official McDonald's China MCP. The agent finds nearby restaurants, menus, bundles and nutrition data, checks promotions and coupons, prices an order with real parameters and shows the amount due. An order is created only after explicit confirmation; the agent does not pay and does not create duplicates. After ordering the skill tracks status and builds a standalone care summary page: orders split by breakfast, lunch, dinner and late night, with no discipline scores or streaks. The author stresses it is a contest entry, not a McDonald's product.
Who it is for. Developers and office workers in China who sit long at code and want to order food through an agent without calorie or self-discipline lectures.
Good fit when
- An agent picks a takeaway lunch near an office in Shenzhen.
- Two bundles are compared with the coupons of a chosen restaurant.
- An order needs tracking and a message when its status changes.
- A summary is built of what time of day food is ordered most often.
Not a fit when
- You need the agent to pay: the skill does not process payment.
- You are outside mainland China: the MCP and orders target McDonald's China.
- The agent must judge food choices by calories: the skill deliberately does not.
Example request
I am in Shenzhen and want pickup at a restaurant, budget 35 yuan. Show suitable options and price them with coupons, but do not place the order.Limitations
A personal token from `open.mcd.cn/mcp` is required (phone login). Keep the token only in a local client. The README describes setup in WorkBuddy and does not mention other clients. A summary page with real orders must be scrubbed of token, phone, address and order number before sharing. The licence is AGPL-3.0. The project is independent and unrelated to McDonald's. The author's checks against the live MCP date from 25 October 2026, and restaurant menus and promotions change over time.
How to disable. Disable `mcd-mcp` in WorkBuddy connectors and delete `~/.workbuddy/skills/mcd-withwork-skills`. Remove the token from the config and reissue it in the console if needed.
FAQ
Where do I get the token?
In the McDonald's China MCP console at `open.mcd.cn/mcp`: phone login, activate and copy the token. Do not commit it to a repository.
Does the agent pay for the order?
No. An order is created only after explicit confirmation, and the skill does not pay or create duplicates.
Can I open the summary page without a token?
Yes. `index.html` holds fictional data: open it by double-click or via `python3 -m http.server 8000`.
How do I connect the MCP?
In WorkBuddy open connectors, then custom connectors and configure MCP, and paste a config modelled on `mcp-config.example.json` with type `streamablehttp` and URL `https://mcp.mcd.cn`.
Which agent is the skill for?
The README describes it for WorkBuddy: MCP setup and skill installation are given only there. Other clients are not mentioned in the README.
Discussion
No questions or reviews yet.
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README in short
The README sets three principles: give facts without judgement, allow not picking the optimum, rely on real data only. The summary page is built from sanitised JSON.