How to Use the DPD MCP in CrewAI

Q: Which DPD tools should my CrewAI team use?

Use the toolfilter option to limit agents to specific actions. This prevents an agent from performing tasks like cancelshipment without authorization.

Deploy a CrewAI team to handle DPD logistics, with specialized agents for tracking, label generation, and carrier coordination.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect DPD MCP to CrewAI

Create your Vinkius account to connect DPD 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.

GDPR Free for Subscribers

Setup DPD with CrewAI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Specialized agent shipping teams

Assign one agent to `create_shipment` and another to `get_manifest`. Your CrewAI team coordinates the entire fulfillment process without manual input. Collaboration happens automatically. One agent prepares the data, and the other confirms the label is ready for the printer.

Automated shipment cancellations

If an order changes, the moderator agent calls `cancel_shipment` to stop the process. This prevents unnecessary labels and shipping costs. Your crew maintains control. It reacts to changes in your order management system in real-time.

Global shipping support

Use `list_countries` to verify destinations before your agents initiate a booking. This saves time by avoiding invalid requests to the carrier. The agents check the rules first. They ensure every shipment complies with the supported regions before acting.

Setup guide

Set up DPD MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. 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 Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke DPD tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="DPD Analyst",
    goal="Access and analyze DPD data via MCP.",
    backstory="Expert analyst with direct DPD access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent DPD transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

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="DPD Analyst",
        goal="Access and analyze DPD data via MCP.",
        backstory="Expert analyst with direct DPD access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent DPD transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

Get your connection token →

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

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect DPD now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about DPD MCP in CrewAI

Include the server URL in your agent configuration. The CrewAI agents will automatically ingest the DPD tool definitions for use.

Yes. Shared memory allows your agents to pass parcel numbers between tasks, making it easy to track status after a shipment is created.

The server uses a zero-trust model. It only touches the parcel-specific metadata required for DPD operations and does not persist your records.

Use the tool_filter option to limit agents to specific actions. This prevents an agent from performing tasks like `cancel_shipment` without authorization.

Use a monitor agent to watch the session logs. It can trigger alerts if any DPD tool returns a status error or an unexpected response.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python