How do I get a DCL Logistics API Key?

Log in to your DCL Logistics eFactory portal and navigate to the API settings or Integrations section to generate your API Key and find your Account ID.

Is inventory data real-time?

Yes, this integration retrieves real-time stock levels directly from DCL warehouse management systems, providing accurate data for your planning.

Can the agent process new RMAs?

This integration currently focuses on monitoring existing orders, shipments, and returns. Initiating new fulfillment orders or RMAs should be handled via the eFactory dashboard.

DCL Logistics MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes

Name: DCL Logistics
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 10 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect DCL Logistics through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

Get MCP Server for AI Agents

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Vinkius supports streamable HTTP and SSE.

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="DCL Logistics Assistant",
            instructions=(
                "You help users interact with DCL Logistics. "
                "You have access to 10 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from DCL Logistics"
        )
        print(result.final_output)

asyncio.run(main())

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About DCL Logistics MCP Server

Integrate DCL Logistics, the leader in third-party logistics (3PL) and fulfillment, directly into your AI workflow. Manage your fulfillment orders, track shipments in real-time, and monitor warehouse inventory levels using natural language.

The OpenAI Agents SDK auto-discovers all 10 tools from DCL Logistics through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries DCL Logistics, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

What you can do

Order Oversight — List and retrieve detailed statuses for all your fulfillment orders across DCL facilities.
Shipment Tracking — Track recent shipments, access carrier details, and monitor delivery progress.
Inventory Management — Check real-time stock levels for your SKUs and identify low-stock items.
Return Processing — Monitor customer returns (RMAs) and their processing status directly via chat.

The DCL Logistics MCP Server exposes 10 tools through the Vinkius. Connect it to OpenAI Agents SDK 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 DCL Logistics to OpenAI Agents SDK via MCP

Follow these steps to integrate the DCL Logistics MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

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

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 10 tools from DCL Logistics

Why Use OpenAI Agents SDK with the DCL Logistics MCP Server

OpenAI Agents SDK provides unique advantages when paired with DCL Logistics through the Model Context Protocol.

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

DCL Logistics + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the DCL Logistics MCP Server delivers measurable value.

Automated workflows: build agents that query DCL Logistics, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries DCL Logistics, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through DCL Logistics tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query DCL Logistics to resolve tickets, look up records, and update statuses without human intervention

DCL Logistics MCP Tools for OpenAI Agents SDK (10)

These 10 tools become available when you connect DCL Logistics to OpenAI Agents SDK via MCP:

get_account_details

Returns account-level metadata such as company name, service tier, and active warehouse assignments. Retrieve metadata for your DCL Logistics account

get_order_details

Resolves line item details, recipient addresses, and the complete audit trail of order processing events. Get detailed information for a specific order

get_shipment_details

Resolves carrier-level status updates, estimated delivery dates, and proof of delivery (if available). Get tracking and shipping details for a specific shipment ID

get_sku_inventory_status

Provides a detailed breakdown of inventory status, including warehouse locations and any pending stock movements. Get current stock level and status for a specific SKU

list_customer_returns

Returns a list of Return Merchandise Authorizations (RMAs) including return reason, status of the returned goods, and credit processing info. List all processed and pending customer returns (RMAs)

list_fulfillment_orders

Returns order metadata including system IDs, current fulfillment status, and customer identifiers. List all fulfillment orders in your DCL account

list_low_stock_items

Identifies SKUs where the available quantity has fallen below the defined reorder point (e.g., < 10 units). Identify items with inventory levels below a threshold (mock logic)

list_recent_shipments

Returns a collection of shipment objects with associated carrier info, tracking numbers, and departure timestamps. List all shipments processed by DCL

list_warehouse_inventory

Returns a list of SKUs with their total on-hand, available, and reserved quantities. List current inventory levels across all items

search_orders_by_keyword

Matches keywords against order references, customer names, and shipping addresses to isolate specific fulfillment records. Search for orders using a keyword or customer name

Example Prompts for DCL Logistics in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with DCL Logistics immediately.

"List all fulfillment orders that are 'Awaiting Shipment'."

"What is the inventory status for SKU 'WR-9988'?"

"Show me the tracking details for shipment 'SHP-1001'."

Troubleshooting DCL Logistics MCP Server with OpenAI Agents SDK

Common issues when connecting DCL Logistics to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

DCL Logistics + OpenAI Agents SDK FAQ

Common questions about integrating DCL Logistics MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.