@striderlabs/mcp-shakeshack
# @striderlabs/mcp-shakeshack
MCP (Model Context Protocol) connector for Shake Shack restaurant. Provides tools for browsing the menu, searching items, finding locations, and getting ordering information.
## Installation
```bash
npm install @striderlabs/mcp-shakeshack
```
## Usage
Add to your MCP client configuration:
```json
{
"mcpServers": {
"shakeshack": {
"command": "npx",
"args": ["-y", "@striderlabs/mcp-shakeshack"]
}
}
}
```
## Available Tools
### `get_menu`
Get the full Shake Shack menu or filter by category.
**Parameters:**
- `category` *(optional)*: Filter by menu category (Burgers, Chicken, Hot Dogs, Crinkle Cut Fries, Frozen Custard, Shakes & Floats, Beer & Wine, Beverages)
### `search_menu`
Search menu items by keyword.
**Parameters:**
- `query` *(required)*: Search term (e.g. "bacon", "vegetarian", "chicken")
### `find_locations`
Find Shake Shack locations by city, neighborhood, or keyword.
**Parameters:**
- `query` *(optional)*: Location search query
- `limit` *(optional)*: Max results to return (default: 5)
### `get_location_details`
Get detailed info for a specific location by ID.
**Parameters:**
- `location_id` *(required)*: Location identifier (e.g. "madison-square-park")
### `get_nutrition_info`
Get nutritional information and allergens for a menu item.
**Parameters:**
- `item_name` *(required)*: Menu item name (e.g. "ShackBurger", "Fries")
### `get_featured_items`
Get current featured and seasonal menu items.
### `get_ordering_info`
Get information about ordering options (app, kiosk, delivery, catering, loyalty).
## Development
```bash
# Install dependencies
npm install
# Build
npm run build
# Run directly
node dist/index.js
```
## License
MIT
TDQS
Scored across 7 tools
Each tool has a clearly distinct purpose with no overlap: find_locations (geographic search), get_featured_items (special menu items), get_location_details (specific location info), get_menu (full menu), get_nutrition_info (nutritional data), get_ordering_info (ordering methods), and search_menu (menu item search). The descriptions reinforce these distinct functions, making tool selection unambiguous.
All tools follow a consistent verb_noun pattern using snake_case: find_locations, get_featured_items, get_location_details, get_menu, get_nutrition_info, get_ordering_info, and search_menu. The verbs 'find', 'get', and 'search' are appropriately used for their respective actions, creating a predictable and readable naming convention throughout.
With 7 tools, the server is well-scoped for its restaurant information domain. Each tool serves a clear purpose (location discovery, menu access, nutrition details, ordering info), and none feel redundant or unnecessary. This count aligns well with typical MCP server ranges (3-15 tools) for focused functionality.
The toolset provides comprehensive coverage for accessing Shake Shack information: locations (find/details), menu (full/featured/search), nutrition, and ordering methods. A minor gap exists in the lack of tools for actual ordering or transaction processing, but given the server's apparent informational focus, this is reasonable. The surface supports common agent workflows without dead ends.