McD-saver

by yuxinlaile · indexed from github

🍟 麦麦省钱助手 —— 麦当劳中国官方 MCP 的省钱点餐 Agent Skill:官方 calculate-price 实时核价 + 券组合优化 + 沉默成本体检与多单用券排程,官方券/套餐/团购券/积分四渠道同口径算终局价。免登录在线试算。

🧪 测试保障:329 个单元测试覆盖 SSE 解析、Token 解析、退避计算、比价决策、 组合优化与 CLI 退出码;demo.py 全链路输出被 tests/test_demo_pipeline.py 断言——demo 即回归测试。

Indexed · not connectedai-infra
Use this agent →

⚡ Use this agent from Claude Code (or any agent)

Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.

Use the MeshKore agent at https://meshkore.com/agent/yuxinlaile-mcd-saver — read its card at https://meshkore.com/agent/yuxinlaile-mcd-saver/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/yuxinlaile-mcd-saver
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/yuxinlaile-mcd-saver/.well-known/agent.json

# 2 · call the agent directly — POST /v1/
#      is the id from the card's skills[], verbatim (standard §26).
#     We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }'

Capabilities

llm

Do you own McD-saver?

This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.