How to Use the Mollie MCP in CrewAI

Q: How do I configure a CrewAI agent to use the Mollie MCP Server?

Pass the Vinkius HTTP URL directly into the mcps list when defining your agent. This gives that specific agent access to tools like createpayment or getcustomer.

Q: Can I restrict which Mollie tools a CrewAI agent can access on the MCP Server?

Yes, use the MCPServerHTTP class with a tool filter to limit access. This prevents your public-facing support agents from triggering refunds or chargeback lists.

Deploy autonomous agent crews using CrewAI and the Mollie MCP Server to manage e-commerce orders and payments.

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Connect Mollie MCP to CrewAI

Create your Vinkius account to connect Mollie 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 Mollie with CrewAI

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Multi-Agent Checkout Operations with CrewAI

`create_payment` is executed by your checkout agent while a separate monitoring agent watches for transaction success. CrewAI coordinates these roles, passing payment details between agents using shared memory. This setup turns manual payment tracking into an autonomous pipeline. If a transaction stalls, the moderator agent takes over to resolve the issue.

Automated Order Audits via MCP Server

`list_orders` lets your auditing crew review recent sales against inventory logs. One agent pulls the order list, while another checks for discrepancies in shipping statuses or line items. You don't have to write custom integration code for this. The agents use the tool directly to fetch the data they need to complete their audit tasks.

Autonomous Chargeback Mitigation Crews

`list_chargebacks` provides the raw data your risk-assessment crew needs to investigate fraud. The research agent pulls the chargeback list, and the analyst agent cross-references it with customer profiles. This team of agents works in the background without human intervention. They flag high-risk accounts and compile reports for your finance team automatically.

Setup guide

Set up Mollie 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 Mollie tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Mollie 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="Mollie Analyst",
        goal="Access and analyze Mollie data via MCP.",
        backstory="Expert analyst with direct Mollie access.",
        tools=mcp_tools,
    )

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

Pass the Vinkius HTTP URL directly into the `mcps` list when defining your agent. This gives that specific agent access to tools like `create_payment` or `get_customer`.

Yes, you can expose the tools to your entire crew. A researcher agent can run `list_payments` while a manager agent uses `get_payment` to verify details.

You can set up sequential execution where one agent creates a payment and another verifies the status. This ensures each step of your checkout pipeline completes in order.

Yes, use the `MCPServerHTTP` class with a tool filter to limit access. This prevents your public-facing support agents from triggering refunds or chargeback lists.

Order details and customer logs are processed entirely in memory during the execution run. Vinkius handles the API requests through a secure, zero-trust sandbox that deletes all session data immediately after use.

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