Does this server support Mollie's Test Mode?

Yes! Simply provide your Test API Key instead of your Live API Key during authentication. The agent will then interact with your test environment.

Can I see exactly what items were in a specific order?

Yes. Use the `get_order` tool with an Order ID (starting with `ord_`). Your agent will return the full breakdown of products, prices, and shipping details.

How do I check for disputed payments?

Use the `list_chargebacks` tool to see a list of all transactions that have been disputed by customers through their banks.

Mollie MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Mollie
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Mollie through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Mollie "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Mollie?"
    )
    print(result.data)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Mollie MCP Server

Connect your Mollie merchant account to your AI agent and take control of your payment workflows and e-commerce operations through natural conversation.

Pydantic AI validates every Mollie tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Payment Tracking — List all transactions and get real-time status updates, amounts, and metadata.
Order Management — View e-commerce orders, including line items and fulfillment status.
Customer Insights — Access customer profiles, payment history, and saved details.
Refunds & Chargebacks — Monitor your refund history and stay informed about disputed payments (chargebacks).
Create Payments — Generate new payment links with custom amounts, currencies, and descriptions.
Deep Inspection — Fetch complete details for specific payments, orders, or customers using their unique IDs.

The Mollie MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI 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 Mollie to Pydantic AI via MCP

Follow these steps to integrate the Mollie MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Mollie with type-safe schemas

Why Use Pydantic AI with the Mollie MCP Server

Pydantic AI provides unique advantages when paired with Mollie through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your Mollie integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Mollie connection logic from agent behavior for testable, maintainable code

Mollie + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Mollie MCP Server delivers measurable value.

Type-safe data pipelines: query Mollie with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Mollie tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Mollie and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Mollie responses and write comprehensive agent tests

Mollie MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Mollie to Pydantic AI via MCP:

create_payment

Create a new Mollie payment

get_customer

g., cst_8wmqcHMN4U). Get specific customer details

get_order

g., ord_st9n7), including line items and shipping info. Get details for a specific order

get_payment

g., tr_7UhVrS0eba). Get details for a specific payment

get_refund

Get specific refund details

list_chargebacks

List payment chargebacks

list_customers

List Mollie customers

list_orders

List all e-commerce orders

list_payments

List all Mollie payments

list_refunds

List all payment refunds

Example Prompts for Mollie in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Mollie immediately.

"List my 5 most recent payments and their current status."

"Create a new payment link for €45.00 for 'Service Invoice #123'."

"Show me my refund history."

Troubleshooting Mollie MCP Server with Pydantic AI

Common issues when connecting Mollie to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Mollie + Pydantic AI FAQ

Common questions about integrating Mollie MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer — your Mollie MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.