Toast API

Overview

Toast is the dominant restaurant POS platform in the United States, used by independent restaurants, fast-casual chains, hotel food and beverage operations, and multi-unit franchise groups. Its platform combines point-of-sale, kitchen display systems, online ordering, payroll, and marketing in a single product, and it processes billions in gross payment volume annually. For restaurant-tech companies building analytics platforms, AI operations tools, and back-office automation, Toast is typically the first integration that enterprise prospects ask about: a substantial share of any US restaurant customer base runs POS through it.

The Toast API exists and covers meaningful POS functionality, but access to production credentials requires completing a formal partner integration agreement. Toast's partner program involves a business development review, agreement terms covering data use and liability, and a credentialing process with a timeline that varies by use case. For a startup validating a new product category before committing to a partner agreement, or an engineering team that needs to ship before a customer goes live, the agreement dependency is not a viable starting point. The sandbox environment is available for development, but it cannot connect to real restaurant data — which means the critical path between a signed customer and a working integration runs directly through Toast's partner approval queue.

Integuru generates a production-ready HTTP API for Toast using direct HTTP requests against the authenticated endpoints the Toast web application uses for its own POS, menu management, and reporting views. The seven planned actions cover orders, menu structure, location configuration, and sales summaries — the complete operational data surface that restaurant-tech products need — without a partner agreement or an approval timeline as a prerequisite.

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Why Teams Need This Integration

The Toast partner approval gap creates a consistent bottleneck across several categories of restaurant-tech product.

Restaurant analytics and AI operations platforms. Tools that ingest order data to generate sales forecasting models, menu performance dashboards, or AI-driven staffing recommendations need list_orders and get_order_detail as live API calls on a schedule tied to the restaurant's service periods. A sales forecasting platform whose customers run POS on Toast cannot deliver meaningful predictions without order-level data updated at the end of each service. The partner approval timeline means many teams cannot build the integration before the customer expects it to be working.

Menu management and digital ordering systems. Multi-channel ordering platforms, ghost kitchen operators, and delivery aggregators need list_menu_items and get_menu to keep their menus synchronized with the Toast system of record. Menu changes — item additions, price updates, modifier adjustments, daypart switches — happen in Toast first. An online ordering system that cannot pull these changes programmatically is forced to ask restaurant operators for manual re-entry on every platform where they take orders, which is the primary source of menu accuracy complaints in multi-channel restaurant operations.

Franchise reporting and management tools. Multi-unit operators and franchise groups need consolidated sales data and location configuration across their full footprint. get_sales_summary and list_locations feed the aggregated reporting views that franchise head offices rely on for daily P&L visibility. A franchise management platform that cannot pull this data programmatically forces operators to export CSVs from each individual location's Toast dashboard, a workflow that does not survive past a dozen sites.

Back-office finance and reconciliation systems. Accounting platforms and finance automation tools that reconcile POS revenue against bank deposits need get_sales_summary on a daily schedule aligned to the restaurant's business day close. Discrepancies between POS totals and bank settlements are easiest to catch the morning after service, not at month end. A reconciliation tool that cannot pull Toast sales data programmatically is working from exports that arrive on the operator's schedule, not the product's.

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Restaurant Workflows This Integration Covers

The seven planned actions cover the order, menu, location, and sales data surfaces that restaurant-tech products need from Toast:

• Order data: list_orders and get_order_detail deliver the full order record including line items, modifiers, applied discounts, payments, and server data for analytics platforms, AI operations tools, and POS reconciliation workflows.
• Menu data: list_menu_items and get_menu surface the complete menu catalog with categories, items, modifier groups, pricing rules, and daypart availability for online ordering systems, menu management platforms, and delivery aggregators.
• Location data: list_locations and get_location_detail provide the location roster and per-location configuration including hours, payment types, and dining options for franchise reporting tools and multi-unit management platforms.
• Sales reporting: get_sales_summary delivers aggregated sales figures including gross sales, net sales, discounts, voids, and tax collected for finance reconciliation systems and franchise P&L dashboards.

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Adjacent Integrations

Integuru already operates across the restaurant and food service vertical in production. The SpotOn integration delivers 9 live actions covering customer listing, settlements, net sales reporting, location management, employee data, and order retrieval for restaurant POS and payments workflows. The Aloha integration provides 4 live actions covering store listing, check search, check detail retrieval, and daily DDV report retrieval for enterprise restaurant POS operators. The Resy integration covers 2 live actions for venue listing and reservation retrieval for reservation management workflows. The MarginEdge integration provides 2 live actions covering order detail and order listing for restaurant food cost and invoice management platforms. All four use the same direct HTTP architecture that the Toast integration will follow.