DHL MCP Server for LangChain 6 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect DHL through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"dhl": {
"transport": "streamable_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,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using DHL, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About DHL MCP Server
What you can do
Connect AI agents to the DHL Express Enterprise API for global supply chain visibility:
LangChain's ecosystem of 500+ components combines seamlessly with DHL through native MCP adapters. Connect 6 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
- Track shipments: Audit real-time checkpoints, transit statuses, and projected delivery hours.
- Get shipping rates: Evaluate instant Express Worldwide and Economy quotes before issuing AWB.
- Create shipments: Dispatch logistics algorithms setting sender/recipient vectors automatically.
- Validate compliance: Certify delivery postal codes mapping to functional address routes cross-border.
- Find service nodes: Query precise GPS mapping of close DHL drop-off or pickup spots.
The DHL MCP Server exposes 6 tools through the Vinkius. Connect it to LangChain 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 DHL to LangChain via MCP
Follow these steps to integrate the DHL MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 6 tools from DHL via MCP
Why Use LangChain with the DHL MCP Server
LangChain provides unique advantages when paired with DHL through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine DHL MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across DHL queries for multi-turn workflows
DHL + LangChain Use Cases
Practical scenarios where LangChain combined with the DHL MCP Server delivers measurable value.
RAG with live data: combine DHL tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query DHL, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain DHL tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every DHL tool call, measure latency, and optimize your agent's performance
DHL MCP Tools for LangChain (6)
These 6 tools become available when you connect DHL to LangChain via MCP:
create_shipment
Requires shipper/recipient details, package weight, and service type. Use this to generate labels for outbound shipments. Returns the tracking number and label document URL. Create a DHL shipment and generate a shipping label
find_locations
Includes address, opening hours, and services available. Use this to find where to drop off a package or visit a DHL center. Find nearby DHL service locations
get_proforma_invoice
Use this for customs clearance documentation or proof of value. Retrieve the proforma invoice document for a DHL shipment
get_rates
g., Express Worldwide, Economy Select) between origin and destination. Requires origin/recipient addresses and package details (weight, dimensions). Use this to compare shipping costs and delivery speeds. Get shipping rates and transit times for DHL services
track_shipment
Returns current status, delivery estimate, and detailed checkpoints (origin, destination, customs, etc.). Requires the 10-digit tracking number (e.g., 1234567890). Use this to monitor international or domestic deliveries. Track a DHL shipment by tracking number
validate_address
Returns standardized address format and suggestions if the address is incorrect. Use this to prevent delivery failures before creating a shipment. Validate a DHL shipping address
Example Prompts for DHL in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with DHL immediately.
"Investigate the real-time exact customs and logistics status for DHL waybill 1928374650."
"Evaluate the logistics rates for sending a 5-kilogram package from ZIP 10001 (US) to ZIP 80331 (DE)."
"Where is the closest official DHL drop-off service center near ZIP 90210?"
Troubleshooting DHL MCP Server with LangChain
Common issues when connecting DHL to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersDHL + LangChain FAQ
Common questions about integrating DHL MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect DHL with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect DHL to LangChain
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.