ScottyLabs MCPs

A unified Model Context Protocol (MCP) server providing access to ScottyLabs's Projects for CMU Students services through FastMCP. This server combines multiple CMU-related services into a single, composable MCP interface.

Overview

This project provides MCP tools for:

• CMU Dining (Eats): Query dining locations, hours, menus, and real-time availability
• CMU Maps: Search buildings, get directions, and calculate distances on campus

Built with FastMCP, this server uses a modular architecture that allows mounting multiple sub-services with namespace prefixes.

Features

CMU Dining Service (eats)

• Get all dining locations with details (cuisine, hours, location)
• Search locations by name
• Find locations currently open
• Check locations open at specific times
• Query locations by cuisine type
• Get detailed hours and specials for specific locations
• Real-time open/closed status
• Online ordering availability indicators

CMU Maps Service (maps)

• Search buildings and locations by name
• Get paths between two locations
• Calculate distances between locations
• List possible location matches for queries

Installation

Prerequisites

• Python 3.11 or higher
• uv or Poetry package manager
• Docker (optional, for containerized deployment)

Using UV (recommended)

# Install dependencies
uv sync

# Activate virtual environment
source .venv/bin/activate

Using Poetry

# Install dependencies
poetry install

# Activate virtual environment
poetry shell

Using Docker

# Build the Docker image
docker build -t mcp-server .

# Run the container
docker run -p 8000:8000 mcp-server

# Or use docker-compose (if you create a docker-compose.yml)
docker-compose up

Usage

Running the Server

The server runs on HTTP transport by default on 0.0.0.0:8001:

# Run as module
python -m mcp_server

# Or run directly
python src/mcp_server/__init__.py

Using Individual Services

Each service can also be run independently:

# Run only the dining service
python src/mcp_server/services/eats/app.py

# Run only the maps service
python src/mcp_server/services/maps/app.py

Available Tools

Dining Tools (prefix: eats)

• get_all_dining_locations(): List all CMU dining locations
• search_dining_locations(name_query): Search by name
• get_locations_open_now(): Find currently open locations
• get_locations_open_at_time(day, hour, minute): Check availability at specific time
• get_location_hours(location_name): Get detailed info for a location
• get_locations_by_cuisine(cuisine_query): Find locations by cuisine type

Maps Tools (prefix: maps)

• search_buildings(query): Search for buildings/locations
• get_path(start_id, end_id): Get path between two locations
• list_possible_locations(query): List location name matches
• distance_between(start_id, end_id): Calculate distance in meters

Configuration

API Endpoints

• Dining API: https://dining.apis.scottylabs.org
• Maps API: https://rust.api.maps.scottylabs.org

Endpoints are configured in:

• src/mcp_server/services/eats/constants.py
• src/mcp_server/services/maps/app.py

Server Configuration

The main server configuration is in src/mcp_server/__init__.py:

• Host: 0.0.0.0
• Port: 8000
• Transport: http (streamable HTTP transport)

CORS Configuration

CORS (Cross-Origin Resource Sharing) is enabled by default in src/mcp_server/core/app.py:

• Allow Origins: * (all origins - adjust for production)
• Allow Methods: All HTTP methods including OPTIONS
• Allow Headers: All headers
• Allow Credentials: Enabled

This configuration enables the server to handle OPTIONS preflight requests and accept requests from any origin. For production deployments, consider restricting allow_origins to specific domains.

Development

Architecture

The project uses a compositional architecture:

1. Base App (core/app.py): Defines the main FastMCP instance
2. Services (services/): Individual MCP services with their own tools
3. Main Composition (main.py): Mounts services with prefixes to avoid conflicts

This allows:

• Independent development and testing of services
• Namespace isolation via prefixes
• Easy addition of new services
• Running services independently or combined

Adding a New Service

1. Create a new directory under src/mcp_server/services/
2. Implement your service with FastMCP tools
3. Mount it in src/mcp_server/main.py:

from mcp_server.services.your_service.app import mcp as your_mcp

main_mcp.mount(your_mcp, prefix="your_service")

Dependencies

Core dependencies:

• fastmcp>=2.12.3: MCP framework
• aiohttp>=3.12.15: Async HTTP client
• httpx: HTTP client for async requests
• pydantic: Data validation and models

Data Models

DiningLocation

• concept_id: Unique identifier
• name: Location name
• short_description: Brief description
• description: Full description
• location: Physical location on campus
• accepts_online_orders: Online ordering availability
• url: Location website
• menu_url: Menu link
• current_status: Open/closed status

TimeSlot

• day: Day of week (0=Sunday, 6=Saturday)
• start_hour: Opening hour (24-hour format)
• start_minute: Opening minute
• end_hour: Closing hour
• end_minute: Closing minute

Output Format

All dining tools return formatted Markdown with:

• Status indicators (=� open, =4 closed)
• Online ordering indicators (=�)
• Grouped by cuisine type
• 12-hour time format
• Consecutive day grouping for hours

Author

AI Team at ScottyLabs

Version

Current version: 0.1.0