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Agentic Commerce MCP Demo

by aharvard

Agentic Commerce MCP Demo (Goose + MCP UI)

A small Model Context Protocol (MCP) server that showcases agentic commerce UX using MCP UI blocks inside Goose. It returns rich, interactive HTML UI for a simple “find restaurants → view menu → fake order → receipt” flow.

Important notes:

  • Demo only. No real sellers, data, payments, or money movement. Everything is synthetic or mocked.
  • Not production code. This exists to demonstrate how MCP UI can drive a click-first agent experience.

Features

  • Streamable HTTP MCP server with multiple tools:
    • find_restaurants – search nearby synthetic restaurants by city/state and query
    • view_restaurant – details card for a restaurant
    • view_menu – menu with images and pricing (mock catalog if “Square” is detected; otherwise a generic menu fallback)
    • order_takeout – interactive order page (edit quantities, remove items)
    • view_receipt – playful, fake receipt
  • Click-first MCP UI: UI dispatches tool calls back to the agent on user actions.
  • Dev HTML previews for local testing at http://127.0.0.1:8000/dev
  • Large, synthetic dataset you can regenerate via scripts

What this is not

  • No live Square API calls, no money movement, no real sellers or PII
  • No persistent storage; no auth; no production hardening

Repo layout

  • src/server.ts – MCP server with tools that render UI
  • src/ui/* – HTML shell, styles, and view builders
  • src/lib/restaurants.ts – local search over synthetic sellers + geocoding via OpenStreetMap Nominatim
  • src/lib/square.ts – tiny mock for “Square detection” and sample catalogs
  • src/data/* – generated JSON for restaurants and category menus
  • src/scripts/* – generators for the data above
  • scenarios.md – example conversational flows and UX notes

Prerequisites

  • Node.js 20+
  • pnpm (bundled with Node) or ppnpm/yarn

Setup

  1. Install dependencies
pnpm install
  1. Generate demo data (optional; the repo includes prebuilt JSON)
# Regenerate synthetic restaurants (5MB+ file) # You can control density: # GEN_MIN_PER_CATEGORY=3 GEN_MAX_PER_CATEGORY=5 pnpm run generate:data pnpm run generate:data # Regenerate generic menus by category pnpm run generate:menus
  1. Run the MCP server (dev)
# Starts an HTTP (streamable) MCP server on 127.0.0.1:8000/mcp pnpm run dev # or pnpm run dev:mcp

Environment variables you can set:

  • MCP_HOST (default: 127.0.0.1)
  • MCP_PORT (default: 8000)
  • MCP_GEOCODE_USERAGENT (default: "mcp-agentic-commerce/1.0 (+https://squareup.com)")
  1. Try the local UI previews in a browser

Use with Goose

This project is designed to be consumed as an MCP extension by Goose.

Option A — Add manually in Goose settings:

  • Open Goose Desktop → Settings → Extensions → Add MCP server
  • Type: HTTP (streamable)
  • URL: http://127.0.0.1:8000/mcp
  • Name: Agentic Commerce MCP Demo
  • Save. Start a new chat and ask something like:
    • “Find coffee around Austin”
    • “Show pizza near Toronto”
    • “Order two lattes from Midtown Bean at 9:15 under Sam.”

Option B — Use the MCP Inspector (handy for testing tools and UI):

# Runs the Inspector against this server pnpm run dev:inspector # Then open the printed Inspector URL; try executing tools directly

Tip: If your model/agent supports MCP UI, it will render the HTML cards, menus, and receipts inline and dispatch tool calls on button clicks.

Tool reference

  • find_restaurants
    • args: city (string, default "Austin"), state (optional), query (optional), limit (1..25, default 10)
    • returns: UI list of nearby sellers; buttons to “Details” and “Order Now”
  • view_restaurant
    • args: business_id (string)
    • returns: UI card with address, hours, phone, website; CTA buttons
  • view_menu
    • args: business_id (string)
    • behavior: if mock "Square" is detected -> use mock catalog; else generic menu by primary category
  • order_takeout
    • args: business_id (string), items (array of { name, qty, price })
    • returns: interactive order table with totals and a Place Order button
  • view_receipt
    • args: business_id (string), items (same as above)
    • returns: playful demo receipt UI

Data notes

  • Restaurants are synthetic and based on seeded generators across many US/CA cities. You can regenerate or reduce the dataset density via env vars on the generator script.
  • Menu images are hotlinked from Unsplash and used only for illustrative purposes in this demo.

Safety and disclaimers

  • For demonstration only; do not treat any information as factual.
  • No money movement occurs. The “Place order” flow only renders a confirmation UI.

Deployment

Deploy to Netlify

This project is configured to deploy as a serverless function on Netlify:

  1. Connect to Netlify:
    • Go to Netlify
    • Click "Add new site" → "Import an existing project"
    • Connect your GitHub repository
  2. Build Settings (auto-detected from netlify.toml):
    • Build command: pnpm run build
    • Publish directory: dist
  3. Deploy:
    • Netlify will automatically deploy on push to main
    • Your MCP server will be available at: https://your-site-name.netlify.app/mcp
    • Dev preview available at: https://your-site-name.netlify.app/dev
  4. Use with Goose (Production):
    • Once deployed, use your Netlify URL in Goose settings
    • Type: HTTP (streamable)
    • URL: https://your-site-name.netlify.app/mcp

License

This project is licensed under the MIT License - see the LICENSE file for details.

-
security - not tested
A
license - permissive license
-
quality - not tested

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Enables interactive restaurant discovery and ordering through a synthetic commerce flow with rich HTML UI. Demonstrates agentic commerce UX with tools to find restaurants, view menus, place mock orders, and generate receipts.

  1. Features
    1. What this is not
      1. Repo layout
        1. Prerequisites
          1. Setup
            1. Use with Goose
              1. Tool reference
                1. Data notes
                  1. Safety and disclaimers
                    1. Deployment
                      1. Deploy to Netlify
                    2. License

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