Lunch Roulette MCP Server
Manages and randomly selects from a list of lunch restaurants, storing choices and visit statistics locally.
Lunch Roulette MCP Server
A Model Context Protocol (MCP) server for managing lunch restaurant choices and picking random restaurants. This server helps you decide where to eat lunch by maintaining a list of restaurants and tracking visit statistics.
Features
Available Tools
- GetRestaurants - List all available restaurants
- AddRestaurant - Add a new restaurant to your choices
- PickRandomRestaurant - Randomly select a restaurant for lunch
- GetVisitStatistics - View statistics about how often you've visited each restaurant
Pre-loaded Restaurants
The server comes pre-loaded with 10 trendy restaurants from the West Hollywood area:
- Guelaguetza - Oaxacan Mexican (3014 W Olympic Blvd)
- Republique - French Bistro (624 S La Brea Ave)
- Night + Market WeHo - Thai Street Food (9041 Sunset Blvd)
- Gracias Madre - Vegan Mexican (8905 Melrose Ave)
- The Ivy - Californian (113 N Robertson Blvd)
- Catch LA - Seafood (8715 Melrose Ave)
- Cecconi's - Italian (8764 Melrose Ave)
- Earls Kitchen + Bar - Global Comfort Food (8730 W Sunset Blvd)
- Pump Restaurant - Mediterranean (8948 Santa Monica Blvd)
- Craig's - American Contemporary (8826 Melrose Ave)
Setup
Prerequisites
- .NET 9.0 SDK or later
- MCP-compatible client (VS Code with GitHub Copilot, Claude Desktop, etc.)
Building
dotnet build
Running
dotnet run
Configuration
VS Code with GitHub Copilot
Add this to your MCP settings:
{
"inputs": [],
"servers": {
"lunchroulette": {
"type": "stdio",
"command": "dotnet",
"args": [
"run",
"--project",
"C:\\GitHub\\LunchRouletteMCP\\LunchTimeMCP\\LunchTimeMCP.csproj"
],
"env": {}
}
}
}
Claude Desktop
Add this to your claude_desktop_config.json:
{
"mcpServers": {
"lunchroulette": {
"command": "dotnet",
"args": [
"run",
"--project",
"C:\\GitHub\\LunchRouletteMCP\\LunchTimeMCP\\LunchTimeMCP.csproj"
]
}
}
}
Usage Examples
Getting All Restaurants
Use the GetRestaurants tool to see all available restaurants in your list.
Adding a New Restaurant
Use the AddRestaurant tool with parameters:
- name: The name of the restaurant
- location: The address or location
- foodType: The type of cuisine (e.g., "Italian", "Mexican", "Thai")
Picking a Random Restaurant
Use the PickRandomRestaurant tool to randomly select a restaurant for lunch. This will also increment the visit counter for that restaurant.
Checking Visit Statistics
Use the GetVisitStatistics tool to see:
- How many times you've visited each restaurant
- Total number of restaurants
- Total number of visits
- Restaurants sorted by visit frequency
Data Storage
The server stores restaurant data and visit statistics in:
- Windows:
%APPDATA%\\LunchTimeMCP\\restaurants.json - macOS/Linux:
~/.config/LunchTimeMCP/restaurants.json
This ensures your data persists between server restarts.
Architecture
The server is built using:
- .NET 9.0 - Runtime platform
- Microsoft.Extensions.Hosting - Application hosting framework
- ModelContextProtocol - MCP server implementation
- System.Text.Json - JSON serialization
Key Components
- RestaurantService - Core business logic for managing restaurants and visit tracking
- RestaurantTools - MCP tool implementations
- Restaurant/RestaurantVisitInfo - Data models
- RestaurantContext - JSON serialization context
Example Interactions
- "Show me all restaurants" → Calls
GetRestaurantstool - "Add a new Italian restaurant called Mario's on Main Street" → Calls
AddRestauranttool - "Pick a random restaurant for lunch" → Calls
PickRandomRestauranttool - "Show me visit statistics" → Calls
GetVisitStatisticstool
Contributing
Feel free to extend the server with additional features like:
- Restaurant ratings
- Cuisine preferences
- Location-based filtering
- Integration with restaurant APIs
- Opening hours tracking
Máy chủ liên quan
Kone.vc
nhà tài trợMonetize your AI agent with contextual product recommendations
СБОРКА Career
Real-time salary data, job market trends, resume review, interview prep, and career advice for the Russian IT market. Powered by hh.ru API.
cookiy
AI-powered user research MCP server for creating studies, generating discussion guides, running AI interviews, recruiting participants, and sharing insight reports.
Acornonaut
Turn YouTube playlists into AI-generated flashcards with spaced repetition — create, search, and export decks via MCP.
ai-memory
Persistent memory for any AI assistant. Zero token cost until recall. Stores memories in local SQLite, ranks by 6-factor scoring, returns results 79% smaller than JSON. Works with Claude, ChatGPT, Grok, Cursor, Windsurf, and any MCP client.
SpotDraft MCP Server
Integrate the SpotDraft API into agentic workflows. Requires SpotDraft API credentials.
Spendlog
Track expenses, income, budgets, and invoices directly in Claude with PDF export and tax reports.
MediaWiki MCP Server
Connect AI assistants to any MediaWiki wiki (Wikipedia, Fandom, corporate wikis) with 33+ tools for search, read, edit, and Markdown conversion.
Unreasonable Thinking Server
A tool for bold and unconventional problem-solving, generating unique solutions by branching and tracking thoughts.
Lattice HQ
Interact with the Lattice performance management platform.
AutoWP
Connects Claude to WordPress sites to create posts and manage sites using the WordPress REST API.