"DoorDash" matching MCP servers:

Enables AI agents to shop on DoorDash through 16 consumer tools covering account and order history, restaurant and menu browsing, cart edits, checkout previews, and order placement (including charging a saved card). It authenticates via a user-launched Chrome session on Windows and encrypts session and operation records with Windows DPAPI.

AI agents can order DoorDash food delivery: search restaurants, browse menus, add items to cart, place orders, and track delivery in real-time.

Enables interaction with the DoorDash Drive API to create, manage, and track delivery requests including quotes, delivery creation, status checks, and cancellations.

Enables AI agents to search restaurants, browse menus, and manage DoorDash carts through structured JSON data. It leverages a background browser to handle authentication and direct GraphQL API calls for efficient interaction.

Enables ordering DoorDash via Poke over text, with tools for restaurant discovery, cart management, promo application, and order submission requiring explicit user confirmation.

Enables AI agents to search restaurants, place delivery orders, and track real-time delivery status using the DoorDash Drive API. It includes a built-in mock data mode that allows for testing and demonstrating delivery lifecycles without requiring live API credentials.

Enables AI agents to quote, schedule, dispatch, and track DoorDash Drive deliveries for restaurants and stores, including staggered batch scheduling for catering runs and launch nights, an operations board, and diagnostics check-ins. Actions that spend money or cancel work require explicit user confirmation, while quotes, tracking, and planning run freely.

Enables AI agents to discover and order food from multiple delivery services (DoorDash, UberEats, Grubhub) using A2A protocol and process payments via Stripe with AP2 protocol mandates for cryptographically signed user authorization.