How to Use the Zippopotam.us MCP in CrewAI

Q: Can I run an operation by postcode with CrewAI?

Yes. You set up a dedicated agent role that uses the lookuppostcode tool, allowing it to retrieve location data and coordinates from Zippopotam.us as part of its workflow.

Run autonomous postal intelligence operations using CrewAI's specialized agents.

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Connect Zippopotam.us MCP to CrewAI

Create your Vinkius account to connect Zippopotam.us 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.

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Setup Zippopotam.us with CrewAI

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Researching Cities with CrewAI

Assign a dedicated Researcher Agent to handle the `lookup_nearby_city` tool. This agent autonomously pulls zip codes for a city and shares that raw data into the shared memory of the crew. This approach lets you build specialized operations where one agent gathers all necessary global postal intelligence from Zippopotam.us.

Analyzing Postcodes with CrewAI

You can assign an Analyst Agent to use `lookup_postcode`. The Analyst reviews the state and coordinates retrieved for a given postcode, then reports findings back to the team. This role-based specialization ensures that Zippopotam.us's complex data is analyzed by the right agent within your autonomous crew.

Autonomous Global Postal Intelligence with CrewAI

The system works as a unified team: one Agent researches using `lookup_nearby_city`, another analyzes the resulting coordinates, and a third Moderator Agent takes action based on that full Zippopotam.us report. This autonomous setup lets you run multi-step operations—from initial lookup to final decision—without human intervention.

Setup guide

Set up Zippopotam.us 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 Zippopotam.us tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

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

    task = Task(
        description="List recent Zippopotam.us 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 Zippopotam.us. 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 Zippopotam.us MCP in CrewAI

CrewAI assigns specific roles within a team to interact with the Zippopotam.us MCP Server. Agents specialize in using tools like `lookup_nearby_city` and `lookup_postcode` to perform tasks autonomously.

Yes. You set up a dedicated agent role that uses the `lookup_postcode` tool, allowing it to retrieve location data and coordinates from Zippopotam.us as part of its workflow.

Yes, you can assign a research agent specifically to use the `lookup_nearby_city` tool. This allows the crew to gather all necessary zip codes and city data into shared memory.

You define a hierarchy of specialized agents. One agent pulls the raw postal code intelligence, another processes it, and a third summarizes the final outcome for you.

The MCP Server touches zip codes, city names, state identifiers, and coordinates. These data points are passed between specialized agents within the crew's shared memory.

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