Jam – Toast MCP Server 🍓🫙

A Model Context Protocol (MCP) server for Toast POS — giving AI agents direct access to restaurant operations: menu management, orders, inventory, labor, delivery integrations, and smart operational insights.

Connect any MCP-compatible AI (Claude, GPT-4, Cursor, Continue, and others) to your Toast account and turn natural language into real POS actions — no dashboard, no manual lookups, no custom integration code.

This project was born out of a simple idea: restaurant owners deserve the same kind of intelligent assistant that enterprise businesses take for granted. Not a chatbot. Not a dashboard. Something that watches your inventory, knows your peak hours, and surfaces insights when you need them most.

We built this as the data layer for an AI co-pilot system. It exposes the Toast API as a clean set of MCP tools that any LLM can call — so instead of logging into Toast, checking stock levels, cross-referencing delivery platforms, and manually updating your menu, you just ask.

What It Does

This server wraps the Toast API into 50+ LLM-callable tools across every major area of restaurant operations:

| Domain | Capabilities | |---|---| | Inventory | Real-time stock levels, low-stock alerts, auto-menu adjustments when ingredients run out | | Orders | Order history, details, void handling, third-party delivery filtering (UberEats, DoorDash, GrubHub, Postmates, Caviar) | | Menu | Browse items, categories, pricing, search functionality | | Labor | Employee management, shift tracking, labor cost visibility | | Analytics | Revenue by period, peak hours, best-selling items, category breakdown | | Financial | Daily/weekly/monthly summaries, tender breakdowns, payment method analysis | | Operations | Open order tracking, void analysis, refund patterns, transaction monitoring | | Retention | Frequent customer identification, lapsed customer detection, win-back messaging | | Forecasting | Week-over-week trends, seasonal patterns, staffing demand signals | | Smart Operations | Stock velocity predictions, peak hour detection, automated ordering recommendations |

Key difference: Unlike other Toast integrations, Jam includes native third-party delivery order tracking with platform-level revenue breakdown — something competitors haven't built.

Tools

Inventory

• get_stock_levels: Full visibility into your ingredients.
• update_stock: Manual corrections after shipments.
• auto_86_item: Instant menu updates for depleted items.
• get_low_stock_items: Automated alerts for reordering.

Menu

• get_menu: Comprehensive menu fetch.
• get_menu_item: Deep dive into specific selections.
• search_menu: Find what you need, fast.

Orders

• get_orders: Monitor recent transactions.
• get_order_details: Audit specific orders.
• void_order: Handle corrections with ease.
• get_delivery_orders: Track third-party delivery orders (UberEats, DoorDash, GrubHub, Postmates, Caviar) with revenue breakdown by platform.

Labor & Staff

• get_employees: Manage your team.
• get_time_entries: Track shifts and labor costs.

Smart Operations

• analyze_stock_needs: Sales-velocity based predictions.
• detect_peak_hours: Staffing optimization intelligence.
• generate_wholesaler_list: Automated shopping list generation based on stock levels.

Getting Started

Prerequisites

• Node.js 24+
• A Toast developer account with API credentials
• Your Toast Restaurant GUID

Install via npm (recommended)

npx @dokdosolutions/toast-mcp

Or install from source

npm install
npm run build

Configure

cp .env.example .env
# Fill in your TOAST_CLIENT_ID, TOAST_CLIENT_SECRET, and TOAST_RESTAURANT_GUID

Run

npm start

Or connect it to your MCP host (like Claude Desktop) using the absolute path to the build:

{
  "mcpServers": {
    "jam": {
      "command": "node",
      "args": ["/absolute/path/to/toast-mcp/dist/index.js"],
      "env": {
        "TOAST_CLIENT_ID": "your_client_id",
        "TOAST_CLIENT_SECRET": "your_client_secret",
        "TOAST_RESTAURANT_GUID": "your_restaurant_guid"
      }
    }
  }
}

Built By

Dokdo Solutions — AI integration for restaurant owners.

License

MIT