How to Use the DHL MCP in CrewAI
Deploy a specialized shipping crew for your logistics. Use CrewAI agents to track, quote, and book DHL shipments.
Works with every AI agent you already use
…and any MCP-compatible client
Connect DHL MCP to CrewAI
Create your Vinkius account to connect DHL to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Autonomous tracking crews in CrewAI
Assign a monitor agent to use `track_shipment` on a loop. It watches for status changes and alerts your team if a delivery stalls. This keeps your operations proactive instead of reactive. Your crew handles the tracking so you don't have to check dashboards manually.
Logistics research agents in CrewAI
Let a research agent use `find_locations` to locate the nearest drop-off point for your drivers. It parses opening hours so you know exactly where to go. It saves your team from digging through site maps. The agent finds the right facility based on the services available.
Multi-step shipping coordination in CrewAI
Create a team where one agent calls `get_rates` and another selects the best option. They share memory to coordinate the entire booking process. This makes your logistics operations autonomous. The crew manages the handoff from quoting to booking without needing your input.
Set up DHL MCP in CrewAI
Prerequisites
- Python 3.10+ installed
-
crewaipackage (pip install crewai) - Active Vinkius subscription with a valid endpoint token
- 1
Install CrewAI
Run
pip install crewaito install the framework. MCP support is built-in via themcpsparameter. - 2
Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the
mcpslist. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically. - 3
Kick off your crew
Create a
Crewwith your agent and tasks. Callcrew.kickoff()— the agent will automatically invoke DHL tools as needed.
from crewai import Agent, Task, Crew
agent = Agent(
role="DHL Analyst",
goal="Access and analyze DHL data via MCP.",
backstory="Expert analyst with direct DHL access.",
mcps=[
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
],
)
task = Task(
description="List recent DHL transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Prerequisites
- Python 3.10+ installed
-
crewai+crewai-toolspackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install crewai crewai-tools. TheMCPServerAdapterhandles lifecycle management and tool conversion. - 2
Connect with MCPServerAdapter
Use
MCPServerAdapteras a context manager withSseServerParameterspointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle. - 3
Assign tools and run
Pass the returned
mcp_toolsto your agent'stoolsparameter. The adapter converts MCP tools to nativeBaseToolobjects compatible with all CrewAI agents.
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters
server_params = SseServerParameters(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
with MCPServerAdapter(server_params) as mcp_tools:
agent = Agent(
role="DHL Analyst",
goal="Access and analyze DHL data via MCP.",
backstory="Expert analyst with direct DHL access.",
tools=mcp_tools,
)
task = Task(
description="List recent DHL transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by DHL. 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.
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Common questions about DHL MCP in CrewAI
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