Uber Eats MCP. Automate every step of your restaurant logistics workflow.
Uber Eats MCP handles all restaurant and delivery operations through your AI client. Use it to monitor incoming orders, update menus instantly, track couriers in real-time, and manage store status across multiple locations. It turns complex manual processes into simple natural language commands.
Give Claude and any AI agent real-world access
View all current orders—pending, accepted, or rejected—to keep a live count of kitchen workload.
Quickly toggle items as available or out of stock and update prices without logging into the merchant portal.
Get live GPS coordinates for delivery couriers and accurate estimated times of arrival.
Move an order from pending to accepted, preparing, ready for pickup, or finally delivered using simple commands.
Pull up full customer details, special instructions, or review documented complaints and refund requests for any specific order.
Check the configuration, status, and unique identifiers for all your registered restaurant locations.
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What AI agents can do with Uber Eats: 14 Tools for Operations Management
These tools let your AI agent perform specific actions across the entire Uber Eats API, from accepting an order to checking a store's operational status.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Uber Eats MCPAccept Order
Accepts a pending order, confirming preparation is starting and triggering courier assignment.
Cancel Order
Cancels an already accepted order for unavoidable reasons, requiring a specific...
Complete Order
Closes the order lifecycle after delivery is confirmed and final payment processing...
Get Delivery Status
Retrieves real-time tracking information for a specific order, including courier...
Get Menus
Fetches the complete list of available items, prices, and IDs for a restaurant's...
Get Order Issues
Pulls up records of customer complaints or reported problems linked to an order ID, along with resolution status.
Get Order
Retrieves complete details for a single specific order, including special instructions and item breakdowns.
Get Orders
Lists all orders across your restaurants, allowing filtering by status like PENDING...
Get Store
Gets detailed information and operational settings for one specific restaurant...
Get Stores
Lists all unique store IDs, names, and addresses associated with your entire...
Mark Order Prep Started
Updates the order status to 'Preparing' and notifies the customer that food is being...
Mark Order Ready
Changes the order status, notifying couriers that the food is packaged and ready for immediate pickup.
Reject Order
Rejects a pending order using specific codes (like 'too_busy') when you cannot fulfill it.
Update Menu Item Availability
Toggles an item's availability status, marking it either in-stock or out-of-stock...
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Uber Eats, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Uber Eats. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS CLOUD
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on each call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
The Daily Manual Grind of Running a Restaurant
Today, when a rush hits, you're juggling multiple screens. You check the order portal for new pings, then switch to your inventory app to see if ingredients are available. Next, you jump into the scheduling tool to manually estimate delivery times and finally, you copy the customer’s name from one system into another just to process a complaint.
With this MCP, those manual switches disappear. You tell your agent what needs doing—like 'We have five pending orders, but we are low on prep staff.' The agent handles the whole sequence: checking capacity, accepting only the viable ones, and marking everything else as unavailable automatically.
Uber Eats MCP: Full Order & Menu Control
You no longer have to manually update statuses or check item IDs. The agent can retrieve all necessary menu data using `get_menus` and then instantly use that information to toggle availability via `update_menu_item_availability`, solving the shortage problem in seconds.
What's different now is control. You move from reacting to alerts to proactively managing logistics, knowing your AI client has full operational oversight of every order stage.
What Uber Eats MCP does for your AI
You can connect your AI agent directly to the full Uber Eats marketplace API. This means you don't have to jump between apps or manually update statuses when things go wrong. You can ask it to monitor all pending orders, check if ingredients are running low by reviewing menu items, and then process them instantly.
Need to handle a large rush? Your agent checks incoming orders for capacity, accepts the ones you can manage, marks others as unavailable, and even notifies the customer with an accurate delay estimate. You can also view detailed order histories to address complaints or track down specific delivery issues. When managing multiple locations, this MCP gives you a central place to check store configurations and monitor everything from one chat window.
It’s housed within Vinkius, giving your agent access to thousands of services so you only connect once.
019d7617-9a5b-73db-b3c3-a7ea56cf0da4 How to set up Uber Eats MCP
The bottom line is: it uses natural language commands to automate core restaurant logistics tasks across multiple systems.
First, connect your Uber Eats merchant account to the MCP using an OAuth token.
Next, tell your AI agent what you need—for example, 'Check all pending orders and accept any that are simple.'
Finally, the agent executes the necessary API calls to update statuses, retrieve data, or modify menus on your behalf.
Who uses Uber Eats MCP
This is for operations managers and multi-location owners who are tired of logging into separate portals just to manage a daily influx of orders. If your job involves rapidly changing menu prices or manually updating statuses during peak dinner rush, this MCP saves you time.
Uses the tool to monitor order queues and quickly adjust restaurant capacity by accepting or rejecting orders in real-time.
Checks store configuration details across all franchise units, ensuring every location has correct delivery settings before opening.
Manages the menu and inventory by updating item availability immediately when specific ingredients run out.
Benefits of connecting Uber Eats MCP
Speed up order intake by letting the agent monitor incoming orders and automatically accepting them if kitchen capacity allows. You don't have to manually review each new ping when dinner service starts.
Maintain inventory accuracy by using update_menu_item_availability to toggle items as out-of-stock immediately, preventing customers from ordering unavailable goods.
Keep customers informed during delays. Use the agent to mark that food preparation has started (mark_order_prep_started) so delivery estimates stay accurate and people don't call in asking where your order is.
Streamline issue resolution by pulling up full details for any order using get_order. You can review special instructions or customer complaints without leaving the chat window.
Manage multiple physical locations from one spot. By calling get_stores, you get a master list of all store IDs needed to run menu updates or check operational status across your entire chain.
Uber Eats MCP use cases
Handling the dinner rush surge
The manager sees 50 pending orders come in during peak hour. Instead of clicking through 50 screens, they ask their agent to review all and accept only those matching capacity limits. The agent uses get_orders followed by multiple calls to accept_order, keeping the kitchen flowing without human bottleneck.
Dealing with supply shortages
The chef runs out of a key topping mid-shift. Instead of calling someone to update the menu, they ask their agent to check the full catalog using get_menus and then immediately use update_menu_item_availability on that specific item.
Investigating an incorrect refund
A customer calls about a disputed charge. The owner asks their agent to pull up the order history using get_order_issues. The agent finds the timestamp of the complaint and the resolution status, giving them concrete data for the conversation.
Pre-opening checklist
A franchise manager needs to verify that all 12 store locations are active. They ask their agent to list all operational sites using get_stores and check each one's specific setup details with get_store before the day begins.
Uber Eats MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Trying to track a delivery without an ID
The user asks, 'Where is my food?' and expects a location update. The agent fails because it needs specific identifiers.
Always start by asking the agent to retrieve the order details using get_order first. Once you have the unique order ID, you can then use get_delivery_status to get real-time tracking.
Attempting mass status changes without filtering
The user asks, 'Accept all orders,' but doesn't specify which statuses are acceptable (e.g., only pending ones). The agent might try to process rejected or completed orders.
Use get_orders first, specifying the status filter you need, like PENDING. This narrows down the list so your agent can accurately use accept_order on only the relevant items.
Updating a menu item without knowing its location ID
The user tries to change an item's price but forgets which store it belongs to. The API call fails because it lacks scope.
You must first list all your sites using get_stores. This provides the necessary external IDs, which you then reference when making menu changes or checking specific store information with get_store.
When to use Uber Eats MCP
Use this MCP if your core business pain point involves real-time logistics management and high-volume transaction flow. Specifically, if you need to react instantly to incoming orders, change inventory status mid-shift, or track couriers live, this is essential. It's built for operational execution.
Don't use this MCP if your goal is deep financial analysis (e.g., calculating quarterly profit margins across 10 years). For that kind of historical data aggregation and complex modeling, a dedicated business intelligence tool or a custom database connection will be better suited. This MCP excels at the 'now'—the immediate workflow tasks like checking order status with get_orders or managing menu availability via update_menu_item_availability. It handles movement, not macroeconomics.
Frequently asked questions about Uber Eats MCP
How do I know if an incoming Uber Eats order was accepted by the restaurant? +
You monitor the status using get_orders. The status changes from PENDING to ACCEPTED when your system successfully accepts the request.
What is the difference between rejecting and canceling an order with Uber Eats MCP? +
Rejecting happens before acceptance (e.g., using reject_order if you are too busy). Canceling happens after acceptance, which usually carries a higher risk of penalties.
Can I check the menu availability for all my locations with Uber Eats MCP? +
No, you must first list all your store IDs using get_stores, and then run get_menus separately for each location ID to get a full catalog.
If I mark an order as ready, what happens next? +
Calling mark_order_ready triggers the system notification that tells couriers your food is packaged and waiting for pickup at your specified location.
How do I check if a customer filed a complaint on an order? +
Use the get_order_issues tool. It pulls up records of complaints, timestamps, and whether a refund has already been issued for that specific transaction.