How do I find my AfterShip API Key?

Log in to your AfterShip account, navigate to **Settings** > **API Keys**. You can generate a new API key there. This key works for both Returns and Tracking APIs.

Can I approve a return request via the agent?

Yes! Use the `approve_return` tool and provide the Return ID. Your agent will update the status in AfterShip, which can also trigger automatic label generation if configured.

Does this support marking items as received?

Yes, you can use the `receive_items` tool to record which items from an RMA have arrived at your warehouse and their current condition grade.

AfterShip Returns MCP Server for CrewAI 4 tools — connect in under 2 minutes

Name: AfterShip Returns
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 4 Tools Framework

Connect your CrewAI agents to AfterShip Returns through Vinkius, pass the Edge URL in the `mcps` parameter and every AfterShip Returns tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="AfterShip Returns Specialist",
    goal="Help users interact with AfterShip Returns effectively",
    backstory=(
        "You are an expert at leveraging AfterShip Returns tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in AfterShip Returns "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 4 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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About AfterShip Returns MCP Server

Connect your AfterShip Returns account to your AI agent to unlock professional returns management and customer experience orchestration. From auditing pending return requests to approving RMAs and generating shipping labels, your agent handles your reverse logistics through natural conversation.

When paired with CrewAI, AfterShip Returns becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call AfterShip Returns tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Return Request Management — List and audit return requests from customers and check their approval status
RMA Orchestration — Retrieve detailed technical metadata for specific RMAs, including item details and reasons for return
Label Generation Support — Monitor shipment creation and retrieve tracking information for return packages
Logistics Oversight — Mark items as received and grade their condition to streamline your warehouse workflow
Process Insights — Quickly identify common return reasons or identify bottlenecks in your return policy directly from chat

The AfterShip Returns MCP Server exposes 4 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect AfterShip Returns to CrewAI via MCP

Follow these steps to integrate the AfterShip Returns MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 4 tools from AfterShip Returns

Why Use CrewAI with the AfterShip Returns MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with AfterShip Returns through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

AfterShip Returns + CrewAI Use Cases

Practical scenarios where CrewAI combined with the AfterShip Returns MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries AfterShip Returns for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries AfterShip Returns, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain AfterShip Returns tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries AfterShip Returns against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

AfterShip Returns MCP Tools for CrewAI (4)

These 4 tools become available when you connect AfterShip Returns to CrewAI via MCP:

approve_return

This allows the customer to ship the item back. Authorize a pending return request to immediately trigger generating the return shipping label

get_return_details

Retrieve the granular items, return reasons, and current logistics status for a specific RMA

list_returns

Retrieve pending or historical customer return requests and their processing statuses

receive_items

Record the arrival and physical grading condition of returned items arriving at the warehouse

Example Prompts for AfterShip Returns in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with AfterShip Returns immediately.

"List all pending return requests from the last 48 hours."

"Approve return request ID 'ret_abc123'."

"Show me details for RMA number 'RMA-98765'."

Troubleshooting AfterShip Returns MCP Server with CrewAI

Common issues when connecting AfterShip Returns to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

AfterShip Returns + CrewAI FAQ

Common questions about integrating AfterShip Returns MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.