How to Use the DPD MCP in LangChain
Get raw DPD shipping data and label generation directly inside your LangChain reasoning loops.
Works with every AI agent you already use
…and any MCP-compatible client
Connect DPD MCP to LangChain
Create your Vinkius account to connect DPD to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Automate multi-step shipping runs with LangChain
This MCP server exposes direct DPD logistics endpoints so your ReAct agents can handle physical fulfillment without human intervention. Your agent calls `create_shipment` to generate a parcel number, feeds that exact output into `get_labels` to fetch the PDF, and prepares the dispatch queue in a single run. You get full visibility into this tool chain via LangSmith tracing. If `get_labels` fails or latency spikes, you see the exact payload that caused the hold-up, allowing you to debug the logistics pipeline instantly.
Resolve routing exceptions on the fly
This DPD toolset allows your agent to use `get_shipment_status` to pull the precise tracking history when a delivery fails. If the issue is an invalid address, the agent queries `list_countries` to check destination rules before prompting the user for corrections. By chaining these tools, the agent handles exceptions programmatically. It can automatically execute `cancel_shipment` for flagged orders and spin up a replacement parcel without manual database lookups.
Dynamic service selection and shop discovery
Your pipeline queries `list_products` to compare available shipping options based on package weight and destination. Once the agent selects the service, it uses `find_parcelshop` to locate the nearest pickup point for the customer. This removes the guesswork from delivery setup. The agent coordinates the entire selection process, generating a manifest via `get_manifest` to hand over to the warehouse staff.
Set up DPD MCP in LangChain
Prerequisites
- Python 3.10+ installed
-
langchain-mcp-adapters+langgraphpackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChainBaseToolobjects. - 2
Connect via HTTP transport
Use
MultiServerMCPClientwith"transport": "http"pointing to your Vinkius endpoint. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. - 3
Create a ReAct agent
Pass the discovered tools to
create_react_agent()from LangGraph. The agent automatically routes DPD tool calls through the MCP protocol. - 4
Run with any LLM
Swap
ChatOpenAIforChatAnthropic,ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.
from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI
async with MultiServerMCPClient({
"dpd-mcp": {
"transport": "http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
result = await agent.ainvoke({
"messages": "List recent DPD transactions"
})
print(result["messages"][-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by DPD. 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.
Why Choose Vinkius
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Common questions about DPD MCP in LangChain
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
Start using the DPD MCP today
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