@striderlabs/mcp-starbucks
MCP server for Starbucks — let AI agents search the menu, customize drinks, find stores, place mobile pickup orders, and manage Starbucks Rewards.
README
@striderlabs/mcp-starbucks
MCP server for Starbucks — let AI agents search the menu, customize drinks, find stores, place mobile pickup orders, and manage Starbucks Rewards.
Features
- Full menu search — search by name, category, or dietary preference (vegan, vegetarian, etc.)
- Item customization — size, milk type, syrups, espresso shots, temperature, foam, and more
- Cart management — add items, view cart, adjust quantities
- Store finder — find nearby Starbucks locations with hours and features
- Mobile ordering — place mobile pickup orders (requires Starbucks account)
- Starbucks Rewards — check Star balance, reward level, and redeem rewards
- Order history — view past orders and quickly reorder favorites
- Session persistence — cookies saved at
~/.striderlabs/starbucks/cookies.json
Installation
npm install -g @striderlabs/mcp-starbucks
npx playwright install chromium
Usage with Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"starbucks": {
"command": "striderlabs-mcp-starbucks",
"env": {
"STARBUCKS_EMAIL": "your-email@example.com",
"STARBUCKS_PASSWORD": "your-password"
}
}
}
}
Credentials can also be passed directly via the starbucks_login tool.
Tools
| Tool | Description |
|---|---|
starbucks_status |
Check connection and login status |
starbucks_login |
Authenticate with Starbucks credentials |
starbucks_logout |
Clear session cookies |
search_menu |
Search menu by name, category, or dietary preference |
get_item_details |
Get full item details and customization options |
customize_item |
Build a customized drink or food order |
add_to_cart |
Add customized item to cart |
view_cart |
View current cart with pricing |
get_nearby_stores |
Find nearby Starbucks locations |
select_store |
Select pickup store |
place_order |
Submit mobile pickup order |
get_order_status |
Track order status and pickup time |
get_rewards |
Check Star balance and available rewards |
redeem_reward |
Apply a reward to current order |
get_order_history |
View past orders |
reorder_favorite |
Quick reorder from a past order |
Example Workflow
1. starbucks_status → check if logged in
2. starbucks_login → authenticate (if needed)
3. search_menu query="latte" → browse menu options
4. get_item_details itemId="hot-latte"
→ see customization options
5. customize_item itemId="hot-latte"
customizations={"size":"grande","milk":"oat","syrup":"vanilla"}
6. add_to_cart quantity=1 → add to cart
7. view_cart → review order
8. get_nearby_stores address="94105"
→ find pickup location
9. select_store storeId="sbux-1001"
10. get_rewards → check available rewards
11. redeem_reward rewardId="reward-123"
→ apply reward (optional)
12. place_order confirm=false → preview order
13. place_order confirm=true → submit order
14. get_order_status → track preparation
Customization Options
Size
short(8 fl oz) — hot drinks onlytall(12 fl oz)grande(16 fl oz)venti_hot(20 fl oz) — hot drinksventi_cold(24 fl oz) — cold drinks
Milk
2percent,nonfat,whole— standard, no chargeoat,almond,coconut,soy— +$0.70
Espresso Roast
signature(Starbucks Signature Espresso Roast)blonde(Blonde Espresso Roast)decaf
Syrups / Flavorings
vanilla, caramel, hazelnut, toffee_nut, cinnamon_dolce, peppermint, sugar_free_vanilla, brown_sugar, mocha, white_mocha
Temperature (hot drinks)
hot, extra_hot, warm, kids_temp
Foam
standard, extra_foam, no_foam, light_foam
Technical Details
- Browser automation: Playwright (Chromium) with stealth patches
- Session persistence: Cookies stored at
~/.striderlabs/starbucks/cookies.json - Transport: MCP stdio
- Ordering: Uses Starbucks web ordering API with Playwright automation fallback
Environment Variables
| Variable | Description |
|---|---|
STARBUCKS_EMAIL |
Starbucks account email (optional — can use starbucks_login tool) |
STARBUCKS_PASSWORD |
Starbucks account password (optional) |
License
MIT — Strider Labs
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。