Swiggy Introduces MCP For Food, Instamart and Dineout

Swiggy Ltd, India’s leading on-demand convenience platform, today announced a major leap in conversational commerce with the launch of Model Context Protocol (MCP) integrations across various business verticals. This rollout, covering Swiggy Food, Instamart, and Dineout, enables users to order groceries, place food orders, and make dining reservations directly through popular AI tools such as ChatGPT, Claude, Google Gemini and others.

With this launch, Instamart becomes the first quick-commerce platform globally to adopt MCP, allowing users to browse and purchase from an assortment of over 40,000 SKUs using simple, natural language prompts.

The Shift to Agentic AI in Commerce

The Model Context Protocol (MCP) is an open-source framework that connects AI systems and chatbots to live data, sources, and services, allowing them to interact securely with external applications. By exposing a secure set of tools via MCP servers, Swiggy allows AI agents to perform complex tasks that previously required navigating multiple app screens. Users can bypass traditional app interfaces and issue intent-based commands. For example, a user can simply type: "Order ingredients needed for Thai green curry." or "Order a highly rated biryani I would love."

The AI agent then handles the entire process: searching for products or restaurants, comparing options, building and updating the cart, applying the best offers or coupons, getting addresses, placing the order, and even tracking delivery. It can also retrieve available booking time slots for a specific restaurant and book a table by creating a cart, applying offers, and confirming the booking in a single prompt.

As users grow more AI-native, increasingly relying on conversational interfaces for planning and decision-making, Swiggy’s integration reflects this shift from static app navigation to dynamic, conversational commerce. This "agentic AI flow" significantly reduces friction by allowing the large language models to handle brand comparisons, quantity selection, and checkout details. The result is a simpler, faster, and more personalized shopping experience that lets users express their intent once and leave it on AI to handle the rest.

Madhusudhan Rao, Chief Technology Officer, Swiggy, said, “India’s convenience needs are deeply contextual, shaped by everyday moments, family routines, personal preferences, and time constraints. Swiggy has always focused on solving for convenience at scale, and conversational commerce takes that a step further by allowing users to simply express what they want, when they want it, whether it is to book a table at their favourite restaurant or order drinks and snacks for a match-viewing party. By bringing MCP to quick commerce, food delivery, and dining out, we’re removing friction from daily decisions and enabling a level of ease, personalisation, and joy that makes on-demand convenience feel effortless.”

Swiggy’s MCP launch builds the foundation for future AI-led experiences, where intelligent agents can act contextually across use cases like meal planning, health goals, dietary preferences, and occasion-based shopping, while remaining privacy-first and secure. In practice, this means users can ask an AI assistant to discover a recipe, identify the right ingredients for four people and add them to their Instamart cart before checking out, build and order a keto or vegan shopping list, compare brands and prices for everyday household staples, or search restaurants and menus, apply relevant offers and book a dine-in table, all through a single, conversational interaction.