MealOS
Enables users to plan meals and place orders across Swiggy Food, Instamart, and Dineout directly from Claude Desktop conversations.
README
MealOS
Cross-server Swiggy meal intelligence — plan, order, and manage meals across Food, Instamart, and Dineout from a single Claude Desktop conversation.
Verified working: placed a live Swiggy order entirely through Claude Desktop chat.
What it does
MealOS is a local MCP server that gives Claude Desktop a unified meal planning brain. Instead of juggling three separate Swiggy apps, you tell Claude what you want and it:
- Plans 21 meals (breakfast/lunch/dinner × 7 days) routing each to the right Swiggy service
- Cook at home → builds an Instamart grocery cart, skipping what's already in your fridge
- Order in → finds a restaurant on Swiggy Food, builds a delivery cart, places the order
- Dine out → finds a free table reservation on Dineout for Friday/Saturday evenings
- Tracks your weekly budget split across all three modes
- Always asks for confirmation before placing any order or booking
Architecture
Claude Desktop (orchestrator)
│
└── mealos MCP server (local stdio)
├── State tools → profile, fridge, weekly plan (~/.mealos/state.json)
├── Food proxy → 14 tools via https://mcp.swiggy.com/food
├── Instamart proxy → 13 tools via https://mcp.swiggy.com/im
└── Dineout proxy → 8 tools via https://mcp.swiggy.com/dineout
Claude Desktop connects to a single local MCP server. That server proxies all 35 Swiggy tools internally using a stored OAuth token — no remote MCP config needed.
Live Order Flow (what actually happens)
You: "Order chicken biryani for dinner"
Claude → mealos: get_addresses → your Hyderabad address
Claude → mealos: search_restaurants → finds open biryani places near you
Claude → mealos: get_restaurant_menu → browses Chaitanya Food Court
Claude → mealos: search_menu → finds Chicken Dum Biryani, shows sizes
You: "Family size"
Claude → mealos: update_food_cart → adds item (menu_item_id + quantity)
Claude → mealos: get_food_cart → shows total, delivery fee, coupon applied
Claude: "Cart total ₹426. Place order?"
You: "Yes"
Claude → mealos: place_food_order → order placed ✅
→ confirmation SMS on your phone
Total time: ~2 minutes. No app switching.
Note on cart visibility: The MCP API uses a separate device session (
deviceId: im-mcp-server) from the Swiggy app. Cart won't show in the app, but placed orders appear in your order history.
MealOS State Tools
| Tool | Description |
|---|---|
mealos_get_context |
Full planning context: profile + fridge + plan + constraints. Call at session start. |
mealos_get_profile / mealos_set_profile |
Read/write preferences: budget, dietary, cook/dine days, location |
mealos_get_fridge / mealos_update_fridge |
Read/write pantry inventory — Instamart skips items already stocked |
mealos_get_plan / mealos_save_plan |
Read/write the current weekly plan |
mealos_update_meal_status |
Mark a meal as confirmed / ordered / skipped |
Swiggy Tools (proxied)
All 35 tools accessible through the single mealos server:
Food (14): get_addresses, search_restaurants, get_restaurant_menu, search_menu, update_food_cart, get_food_cart, flush_food_cart, fetch_food_coupons, apply_food_coupon, place_food_order, get_food_orders, get_food_order_details, track_food_order, report_error
Instamart (13): search_products, your_go_to_items, update_cart, get_cart, clear_cart, checkout, get_orders, get_order_details, track_order, create_address, delete_address
Dineout (8): get_saved_locations, search_restaurants_dineout, get_restaurant_details, get_available_slots, book_table, get_booking_status
Built-in Prompts
Use these from the Claude Desktop prompt picker (/ in chat):
plan_week— Generate a full weekly meal plan across all three Swiggy servicesquick_order— Place a food delivery order right nowrestock_groceries— Restock the fridge via Instamartbook_dinner— Find and book a free restaurant table for dinner
Setup
Prerequisites
- Claude Desktop
- Node.js 18+
- A Swiggy account with Builders Club API access
1. Clone and install
git clone https://github.com/naga-pavan12/mealOS.git
cd mealOS
npm install
2. Authenticate with Swiggy
npx tsx src/auth-cli.ts
This opens your browser for Swiggy OAuth login. Token saves to ~/.mealos/auth.json. Only needed once — token auto-refreshes.
3. Build and deploy the MCP server
npm run build
mkdir -p ~/.mealos
cp dist/mcp-server.mjs ~/.mealos/mcp-server.mjs
Why
~/.mealos/? Claude Desktop on macOS sandboxes spawned processes and blocks file reads from~/Downloads. The bundle must live outside Downloads.
4. Configure Claude Desktop
Edit ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"mealos": {
"command": "/opt/homebrew/bin/node",
"args": ["/Users/YOUR_USERNAME/.mealos/mcp-server.mjs"]
}
}
}
5. Restart Claude Desktop
mealos should appear as connected under Settings → Developer. You'll see 39 tools available.
6. Set up your profile (first time)
Tell Claude:
"Set up my MealOS profile. Budget ₹3000/week, non-veg, household of 1, cook on Mon/Wed/Sat, dine out Fri/Sat. I'm in [your city]."
Then add your fridge:
"Update my fridge: I have 500g chicken, 1kg rice, 4 eggs, some garlic."
State storage
All state is stored locally — no cloud sync, no external database.
~/.mealos/
├── mcp-server.mjs ← compiled bundle (from dist/)
├── state.json ← profile, fridge inventory, weekly plan
├── auth.json ← Swiggy OAuth token (chmod 0600)
└── registration.json ← OAuth client ID
Swiggy Constraints
Key limits baked into the planning rules:
| Constraint | Limit |
|---|---|
| Cart cap | ₹1000 per order (Food + Instamart) |
| Instamart minimum | ₹99 |
| Payment method | COD only (Food, v1) |
| Dineout bookings | Free only (isFree=true, bookingPrice=0) |
| Confirmation | Required before every order and booking |
| Order retry | Not idempotent — check order history before retrying |
Development
npm run build # bundle src/mcp-server.ts → dist/mcp-server.mjs
npm run typecheck # type-check without emitting
npx tsx src/auth-cli.ts # re-authenticate with Swiggy
After any code change: npm run build → cp dist/mcp-server.mjs ~/.mealos/ → restart Claude Desktop.
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。
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。
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。
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。
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。
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。
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。