Quest Apartment Hotels — MCP Server (POC)

A Model Context Protocol (MCP) server for Quest Apartment Hotels, enabling AI assistants (ChatGPT, Claude, Gemini) to search properties, check availability, compare rates, and make bookings across Quest's Australian portfolio.

POC Note: Availability and rates are simulated with deterministic fake data. Bookings are stored in-memory and reset on each cold start.

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Tools Exposed

Tool	Description
quest_search_properties	Find properties by city, state, or amenity
quest_get_property_details	Full details for a specific property
quest_check_availability	Availability for a property and date range
quest_get_rates	Rate plans for a property and stay
quest_search_availability	Combined search + availability in one call
quest_get_booking_quote	Price estimate without creating a booking
quest_create_booking	Make a reservation
quest_get_booking	Look up an existing booking by confirmation number

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Project Structure

Quest-MCP/
├── api/
│   └── mcp.ts          # All server logic (single file)
├── package.json
├── tsconfig.json
├── vercel.json          # Routes /mcp → /api/mcp
└── .gitignore

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Local Development

Prerequisites

• Node.js 20+
• Vercel CLI (installed as a dev dependency)

Setup

# Clone the repo
git clone https://github.com/YOUR_USERNAME/Quest-MCP.git
cd Quest-MCP

# Install dependencies
npm install

# Type-check (no output = success)
npm run build

# Start local dev server
npm run dev

The server will be available at http://localhost:3000/mcp.

Testing locally with MCP Inspector

npx @modelcontextprotocol/inspector

Set the URL to http://localhost:3000/mcp and transport to Streamable HTTP.

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Deployment (Vercel via GitHub)

The project is configured to auto-deploy to Vercel on every push to main.

First-time setup

1. Push this repo to GitHub
2. Go to vercel.com → Add New Project → Import your GitHub repo
3. Vercel will auto-detect the project — no extra config needed
4. Click Deploy

After the first deploy, every git push to main triggers a new deployment automatically.

Your MCP endpoint will be at:

https://YOUR-PROJECT.vercel.app/mcp

Environment Variables

None required for this POC. All data is hardcoded.

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Testing in OpenAI ChatGPT

Per the OpenAI MCP testing instructions:

1. Open chatgpt.com and start a new conversation
2. Click the Tools (plug) icon → Add a tool → MCP Server
3. Enter your Vercel URL:

   https://YOUR-PROJECT.vercel.app/mcp
   

4. Set approval to No approval required (for testing)
5. Click Connect

ChatGPT will discover all 8 tools automatically. Try prompts like:

• "Find me a Quest hotel in Melbourne for 3 nights from next Friday"
• "What Quest properties in Sydney have a gym?"
• "Check availability at Quest Docklands for 15–18 March 2025 and give me the best rate"
• "Book a studio at Quest on William for 2 nights from March 20, name John Smith"

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Sample Data

The server includes 27 real Quest Australia properties across:

State	Count
VIC	7
NSW	6
QLD	4
ACT	2
WA	3
SA	1
NT	1
TAS	1
Regional	2

Simulated Rate Plans

Code	Description	Adjustment
FLEX	Flexible rate	+10%
STD	Standard rate	base
ADVP	Advance purchase (7d+)	−10%
CORP	Corporate rate	−15%
LONG7	Weekly rate (7+ nights)	−15%

Weekend surcharge: +20% on Fri/Sat/Sun nights.

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Architecture Notes

• Transport: Streamable HTTP (stateless — required for Vercel serverless)
• Sessions: Disabled (sessionIdGenerator: undefined) — each request is independent
• CORS: Open (*) — required for browser-based AI clients
• Availability: Deterministic hash on propertyId|date|roomType → 75% available
• Bookings: In-memory Record<string, Booking> — resets on cold start

For a production implementation, replace the in-memory store with a database and connect to Quest's RMS API.