AfterShip Returns MCP. Manage every return request from start to finish.
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AfterShip Returns automates your entire reverse logistics pipeline. Use this MCP to manage return requests, audit RMAs, approve returns, and process item receipts—all through natural conversation with your AI client.
Stop manually checking statuses; get full visibility into every step of the customer's return journey.
What your AI agents can do
Approve return
Authorizes an awaiting return request, immediately generating the necessary shipping label for the customer to send the item back.
Get return details
Retrieves comprehensive information on a specific RMA, detailing items, original reasons for return, and current logistics status.
List returns
Gathers lists of customer returns, showing both pending inquiries and past requests along with their processing statuses.
List and check the status of customer returns both pending and historical.
Retrieve technical metadata for a specific Return Merchandise Authorization, including item lists and stated reasons for return.
Approve pending requests instantly, triggering the generation of required shipping labels.
Record that items have arrived at the warehouse and assign them a grading condition for restocking purposes.
Ask AI about this MCP
Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
AfterShip Returns: 4 Tools
These tools let you programmatically list returns, get detailed item information, approve shipments, and record physical goods received.
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 AfterShip Returns on Vinkius019d7549approve return
Authorizes an awaiting return request, immediately generating the necessary shipping label for the customer to send the item back.
019d7549get return details
Retrieves comprehensive information on a specific RMA, detailing items, original reasons for return, and current logistics status.
019d7549list returns
Gathers lists of customer returns, showing both pending inquiries and past requests along with their processing statuses.
019d7549receive items
Logs the arrival of physical goods at the facility, recording their condition and grading for inventory purposes.
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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 4 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
The manual return audit loop shouldn't slow you down.
Today, processing a batch of returns means jumping through hoops. You start by checking the main dashboard for pending requests, then copy-pasting RMA numbers into another system to get item details. If it passes validation, you open yet a third portal to generate the shipping label. It's tedious, slow, and prone to human error every time.
With this MCP, those manual steps disappear. You simply ask your AI agent for help tracking returns. The agent pulls all necessary data—the request status, item specs, and approval requirements—and gives you a consolidated answer in seconds.
The AfterShip Returns MCP provides full cycle control.
The biggest time sink is the gap between digital approval and physical receipt. You might approve a return using `approve_return`, but if staff fail to use `receive_items` upon arrival, your inventory count will be wrong, and you'll lose track of the item’s condition.
This MCP forces completeness. It connects authorization with operational reality. When you use this toolset, you guarantee that every step—from initial audit via `list_returns` to final grading via `receive_items`—is accounted for in one place.
What you can do with this MCP connector
Handling product returns used to be a bureaucratic nightmare. You'd have to jump between multiple tabs just to check if a request was pending, confirm the item details against an RMA number, and then generate a label before finally marking it as received in your warehouse system. This MCP changes that process entirely.
Your AI agent manages all of this orchestration—from initial customer inquiry to physical inventory update—using simple chat commands. It acts as a central nervous system for your returns flow. Connecting to the Vinkius catalog makes these advanced capabilities instantly available to any compatible client, letting you automate complex reverse logistics processes without writing a single line of code.
019d7549-4468-7391-8002-2a1a091515e0 
How AfterShip Returns MCP Works
- 1 Subscribe to this MCP and enter your AfterShip API Key.
- 2 Connect your AI client (Claude, Cursor, etc.) to Vinkius and activate the returns toolset.
- 3 Ask your agent a question like: 'What's the status for RMA-98765?' The system executes the necessary checks and provides a consolidated answer.
The bottom line is you stop navigating multiple systems. You ask your AI client, and it handles the data flow across all required logistics endpoints.
Who Is AfterShip Returns MCP For?
E-commerce Operations Managers who are tired of spending hours cross-referencing spreadsheets to track where a returned item is stuck in the cycle. Logistics Coordinators needing instant visibility into inventory condition and Customer Support Agents who need immediate, accurate return status updates for customers.
Automating approval workflows to ensure fast customer resolution while maintaining strict compliance on RMA tracking.
Marking received items and assigning their final grading condition without needing manual data entry into the system.
Quickly looking up a customer's full return history, including the item details and current tracking status, in one chat session.
What Changes When You Connect
- Stop guessing on status. Use
list_returnsto pull up a full list of pending or historical requests and see exactly where each one is stuck in the pipeline. - Save time investigating returns. Instead of checking multiple databases, use
get_return_detailsto instantly find item specifics and the original reason for return on any RMA number. - Close the loop on approvals. When a request is ready, call
approve_return. This single action notifies the customer and automatically generates the required shipping label. - Streamline your warehouse process. Use
receive_itemsto record when goods arrive at the facility, assigning them a grading condition right from the chat interface. - Improve visibility across departments. By automating the entire flow—from viewing status with
list_returnsto confirming receipt withreceive_items—you give both support and warehouse staff clear data.
Real-World Use Cases
A customer asks for a return on a defective item.
The agent first uses list_returns to confirm the request exists. Next, they run get_return_details to verify the exact item and defect reason. If everything checks out, they execute approve_return, telling the customer immediately that their label is ready. This whole process takes seconds.
The warehouse receives a batch of returned products.
Instead of having staff manually enter data into a sheet, the ops manager simply tells the AI agent to run receive_items. The system logs the items and confirms their grade (e.g., 'Good' or 'Needs Repair'), updating inventory automatically.
A customer complains about delayed tracking.
Support uses the MCP to quickly check the return status using list_returns and then calls get_return_details. The agent can immediately tell the customer not only that the request is approved, but also what the specific item details are.
A bulk of returns needs processing after a sale.
The e-commerce team uses list_returns to pull all pending requests from the last week. They can then systematically use get_return_details on each one, identifying patterns or bottlenecks in the return policy before approving them.
The Tradeoffs
Checking status piecemeal
Manually checking the main dashboard for pending requests, then opening a secondary tab to view item details, and finally logging into a third system just to generate the label.
→
Start by using list_returns to see all statuses. Then use get_return_details on any specific RMA you need to investigate. Once confirmed, trigger the action with approve_return.
Ignoring physical receipt steps
Approving a return and generating a label is step one. If warehouse staff forget to log the item arrival, the inventory remains inaccurate, causing fulfillment issues later.
→
Always remember the final stage. After approval and shipment, use receive_items when the goods physically arrive at your facility.
Over-relying on single data points
Seeing only that a request is 'Pending' from the main dashboard isn't enough. You need to know why it's pending or what items are involved.
→
Don't just look at the status. Always follow up by calling get_return_details first. This gives you granular data on item specifics and return reasons.
When It Fits, When It Doesn't
Use this MCP if your core problem is managing the complex, sequential handoffs inherent in reverse logistics—from customer request to warehouse receipt. You need a system that handles visibility (list_returns), investigation (get_return_details), authorization (approve_return), and physical confirmation (receive_items) all within one conversation thread. Don't use this if you just need basic shipping label generation; those simpler tools won't account for the initial request auditing or the final inventory grading needed to complete the cycle. You should also avoid it if your returns process is simple enough that a single, dedicated SaaS tool handles everything end-to-end without needing AI orchestration.
Common Questions About AfterShip Returns MCP
How do I check the status of all returns using list_returns? +
Use list_returns when you need an overview. This tool pulls up both pending and historical requests, giving you a quick dashboard view of where every customer return stands.
Do I need to use get_return_details before approving returns? +
Yes. Always call get_return_details first. This ensures you have the full context—item list and specific return reasons—before committing to an approval via approve_return.
What if I approve a return but items aren't received? Do I still need receive_items? +
Yes. Even after approving the initial request, you must use receive_items when the goods physically arrive at your warehouse to log them and record their condition.
Can this MCP help me process returns for a specific RMA number? +
Absolutely. You can check details using get_return_details, then if approved, trigger the label generation with approve_return all from one prompt.
What specific permissions are required to run `approve_return`? +
The API key needs read and write scopes. This ensures your agent can not only verify the request status but also trigger the actual label generation process successfully.
If running `list_returns`, what filters can I apply to narrow down results? +
You can filter by date range and specific statuses like 'Pending' or 'Overdue'. This prevents you from having to manually sift through months of historical return data.
If the `approve_return` tool fails, how do I troubleshoot the error? +
Check the provided error message for invalid IDs or required steps. Often, running get_return_details first confirms if all necessary item information is present before attempting approval.
Does calling `receive_items` automatically update external customer records? +
No, using receive_items updates the internal grade and arrival date. If you need to notify a customer or trigger an action outside of AfterShip's system, you must follow up with your own notification tool.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.