Dada Now Delivery MCP. Manage P2P deliveries, from quote to complaint.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Dada Now Delivery gives your AI agent direct access to local courier services. You can schedule deliveries, calculate real-time fees, manage pickup shops, and even handle post-delivery issues like adding tips or filing complaints.
It gives your LLM the capability to act as an autonomous fleet coordinator for P2P logistics.
What your AI agents can do
Add complaint
Submits a formal complaint about a specific driver's performance or behavior.
Add order
Creates and dispatches a brand new Dada delivery order.
Add shop
Registers a new pickup hub or store location on the Dada network.
The agent runs query_order_fee to calculate the expected cost before an order is placed.
The agent uses add_order to dispatch a new delivery and cancel_order to halt an existing dispatch.
The agent can apply a tip using add_tip or file a complaint against a driver using add_complaint.
The agent checks live status with query_order_status or attempts to restore a failed dispatch using readd_order.
The agent registers new hubs with add_shop or modifies existing shop details with update_shop.
The agent retrieves necessary Dada City Codes using get_city_code.
Ask AI about this MCP
Supported MCP Clients
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019d842cadd complaint
Submits a formal complaint about a specific driver's performance or behavior.
019d842cadd order
Creates and dispatches a brand new Dada delivery order.
019d842cadd shop
Registers a new pickup hub or store location on the Dada network.
019d842cadd tip
Adds a specific monetary tip to an existing delivery order.
019d842ccancel order
Cancels a delivery dispatch before the courier picks up the goods.
019d842cget city code
Retrieves necessary Dada City Codes needed for accurate delivery routing.
019d842cquery order fee
Calculates the estimated delivery fee for a specific route before committing to an order.
019d842cquery order status
Gets the live, up-to-the-minute tracking status for a specific order.
019d842creadd order
Restores a delivery order that has expired or failed to process.
019d842cupdate shop
Modifies the details of an already registered pickup shop or station.
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 every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Dada Now Delivery, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
Yo, Dada Now Delivery gives your AI agent direct access to local courier services. It lets your agent function like an autonomous fleet coordinator for P2P logistics. You can't imagine the time savings.
Getting the Job Done:
- Planning & Fees: Before your agent sends a single thing out, it'll run
query_order_feeto calculate the expected delivery cost for any route. When you're ready, it usesadd_orderto dispatch a brand new Dada delivery, and if you change your mind, it can stop the whole thing withcancel_order. You gotta grab the necessary Dada City Codes first; your agent runsget_city_codefor accurate routing. - Tracking & Fixing Issues: Your agent keeps you in the loop by checking the live status with
query_order_status. If a delivery fails or expires, it can usereadd_orderto restore the dispatch. If something goes sideways with a driver, it'll useadd_complaintto file a formal complaint about the performance or behavior. You can also slide a tip on the order usingadd_tip. - Managing Locations: If you're setting up new hubs, your agent registers them with
add_shop. If an existing shop's details change, it updates them usingupdate_shop.
This whole setup means your AI client doesn't just talk about logistics—it does it. It's a direct line to the operational side of Dada Now.
How Dada Now Delivery MCP Works
- 1 Sign up on the Dada Now Developer Program to get your App Key, App Secret, and Source ID.
- 2 Input these credentials safely into Vurb.
- 3 Your AI client sends a request. The backend handles the required signature rules and timestamps, letting your LLM focus only on the delivery request.
The bottom line is, your AI agent talks naturally to the platform, and the Vurb backend handles the complex, technical API calls.
Who Is Dada Now Delivery MCP For?
Operations managers, e-commerce chatbot developers, and logistics coordinators who are tired of manually logging into multiple dashboards to fulfill a simple delivery request. If your team needs to manage real-world, high-volume, on-demand logistics, this is for you.
Builds bots that dispatch local couriers directly from customer chat conversations without needing a dedicated backend server.
Uses the agent to control the Dada dashboard via natural language, allowing non-technical staff to manage orders, complaints, and shop registrations.
Tests multi-step fulfillment scenarios, like calculating query_order_fee before advising on an add_order.
What Changes When You Connect
- Automated Ordering Cycle: You can build a full order flow in one go. First, your agent checks the cost with
query_order_fee. Then, it creates the delivery usingadd_order. This eliminates the need for multiple, sequential API calls. - Real-Time Status Updates: Instead of checking a dashboard, your agent monitors the shipment using
query_order_status. If the status changes (e.g., 'In Transit'), your agent knows immediately and can respond to the user. - On-the-Fly Adjustments: Delivery plans change fast. If you need to change the pick-up spot, your agent can run
add_shop. If you need to pay the driver, it usesadd_tipto adjust the order total. - Operational Resilience: Did the order fail or expire? Your agent doesn't stop. It can run
readd_orderto bring the shipment back into the active pipeline, saving manual recovery time. - Complaint Management: The system handles post-delivery issues. If the driver was late, your agent files the issue using
add_complaint, closing the loop on the customer experience. - Hub Maintenance: Keep your network running smoothly. Your agent can register new local hubs with
add_shopor correct old details withupdate_shopwithout a human logging into the backend.
Real-World Use Cases
Customer asks, 'How much is this delivery?'
The customer asks their chatbot to deliver a package. The agent intercepts this, runs query_order_fee to get the cost. It reports the estimate (e.g., ¥ 12.00) and then asks the user if they want to proceed to add_order. The problem is solved in one conversation.
The store location changed, needs updating.
A store manager needs to update the address for a pickup hub. Instead of logging into the web portal, the manager simply prompts their agent: 'Update Shop XYZ details.' The agent runs update_shop, immediately correcting the local network data.
The order was canceled but needs to be re-opened.
An order was dispatched but then got canceled due to a scheduling conflict. The agent runs cancel_order first, confirming the cancellation, and then immediately runs readd_order to put the delivery back into the active queue.
We need to track a package that stalled.
The user says, 'Where is my order?' The agent runs query_order_status to get the live tracking data. If the status is 'Stalled,' the agent can then use add_complaint to automatically flag the issue for review.
The Tradeoffs
Using multiple APIs for basic status checks
A developer writes code that calls a simple GET endpoint to check status, then another endpoint to check fees, and a third to see the nearest shop code. This creates tight coupling and fails if any single endpoint is down.
→
Always use the dedicated tools. For status, use query_order_status. Before an order, check the cost with query_order_fee. If you need location data, use get_city_code first.
Ignoring the order lifecycle
A user calls add_order but forgets to check if the shop is registered. The delivery fails because the pickup location is invalid, forcing a manual fix.
→
Always validate the location first. Run add_shop or update_shop to ensure the hub is registered. Then, check the cost using query_order_fee before calling add_order.
Handling post-delivery fixes manually
When a customer complains, a human has to log into the dashboard, find the order, and manually file the complaint in a separate system. This takes minutes of back-and-forth.
→
Let your agent handle the follow-through. After the delivery, the agent uses add_complaint and can even send a thank-you tip with add_tip using a single prompt.
When It Fits, When It Doesn't
Use this MCP Server if your business logic requires managing complex, multi-step, real-world logistics processes. Specifically, you need to coordinate actions like estimating cost (query_order_fee), creating orders (add_order), and then handling post-delivery issues (add_complaint). You're dealing with dynamic, physical movement of goods.
Don't use this if you only need simple CRUD operations on static data (e.g., just listing shops). For that, a simple database connector would work. If your core need is just tracking, query_order_status is enough. But if you need to act on that status (like canceling or adding a tip), you need the full suite of tools.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Dada Now. 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.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Managing deliveries used to mean jumping between six different web portals.
Before this, dispatching an order was a manual nightmare. You'd log into the shop portal to register a new location, then switch to the ordering dashboard to create the job. After the job was done, you'd hop to the complaint system if something went wrong. Every failure meant copying an ID and pasting it into a different system.
Now, your agent manages the whole sequence. You just tell it, 'Deliver X to Y.' The agent runs `query_order_fee` to check the price, uses `add_order` to dispatch the courier, and keeps track of the whole thing. The whole process is managed in one conversation.
Dada Now Delivery MCP Server: Order & Logistics Ops
You eliminate the need for manual checks. Instead of running separate reports for status, fees, and available shops, your agent runs `query_order_status` and `query_order_fee` together. It gives you a single, consistent view of the entire logistics chain.
The difference is control. You don't just read data; you *act* on it. You tell the agent to cancel the order with `cancel_order`, and it executes the full process. It's that level of direct, conversational control that changes everything.
Common Questions About Dada Now Delivery MCP
How do I check the cost of a delivery using Dada Now Delivery MCP Server? +
Use the query_order_fee tool. This estimates the delivery cost before you commit to dispatching the order, so you know the fee upfront.
Can I add a tip to an order with the Dada Now Delivery MCP Server? +
Yes, use the add_tip tool. This tool lets you add a specific monetary tip to an order after it's been created.
What if my order fails or expires? +
Run the readd_order tool. This mechanism restores a delivery order that has failed or expired, putting it back into the active dispatch flow.
Is the Dada Now Delivery MCP Server only for new orders? +
No. You can manage the entire lifecycle. You can use add_complaint after delivery, and you can use add_shop to register new hubs.
How do I use the `add_shop` tool in the Dada Now Delivery MCP Server? +
You register new pickup hubs by providing the desired shop name and location details. This tool allows you to create new delivery pickup points directly via natural language prompts.
Can the Dada Now Delivery MCP Server handle order cancellations using `cancel_order`? +
Yes, you can cancel a delivery dispatch by specifying the order ID. This function stops an active delivery before it reaches its destination.
What is the role of the `query_order_status` tool in the Dada Now Delivery MCP Server? +
The query_order_status tool retrieves the live tracking status for any order. Use it to get real-time updates on where a delivery is located.
Does the Dada Now Delivery MCP Server support updating station details using `update_shop`? +
Yes, you can update existing station details using the update_shop tool. This lets you maintain accurate information for your existing delivery hubs.
Is the MD5 signature abstracted? +
Yes! The parameters like timestamp, app_key, v, and format are automatically concatenated. The backend performs the MD5 check and injects the signature transparently to the LLM context, yielding flawless delivery logs.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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