Mollie MCP Server for Pydantic AIGive Pydantic AI instant access to 7 tools to Create Payment, Get Payment Details, List Customer Subscriptions, and more

Name: Mollie
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

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

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The Mollie MCP Server for Pydantic AI is a standout in the Money Moves category — giving your AI agent 7 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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+ other MCP clients

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 "
            "(7 tools)."
        ),
    )

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

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

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 account to any AI agent and manage European payments through natural conversation.

Pydantic AI validates every Mollie tool response against typed schemas, catching data inconsistencies at build time. Connect 7 tools through 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 Management — Create, list, and inspect payments with full status details
Refund Tracking — Browse all processed refunds
Customer Management — List registered customers for recurring billing
Subscriptions — View active and cancelled subscriptions per customer
Payment Methods — List all enabled payment methods (iDEAL, Bancontact, cards, etc.)

The Mollie MCP Server exposes 7 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 7 Mollie tools available for Pydantic AI

When Pydantic AI connects to Mollie through Vinkius, your AI agent gets direct access to every tool listed below — spanning payment-gateway, recurring-billing, refund-management, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

create

Create payment on Mollie

Create a new payment

get

Get payment details on Mollie

Get details for a specific payment

list

List customer subscriptions on Mollie

List subscriptions for a customer

list

List customers on Mollie

List Mollie customers

list

List payment methods on Mollie

List available payment methods

list

List payments on Mollie

List Mollie payments

list

List refunds on Mollie

List all refunds

Connect Mollie to Pydantic AI via MCP

Follow these steps to wire Mollie into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 7 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

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 recent payments and their statuses."

"Create a payment of €50 for a premium upgrade."

"Show enabled payment methods and list refunds."

Troubleshooting Mollie MCP Server with Pydantic AI

Common issues when connecting Mollie to Pydantic AI through 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.