Mollie MCP Server for LangChainGive LangChain instant access to 7 tools to Create Payment, Get Payment Details, List Customer Subscriptions, and more
LangChain is the leading Python framework for composable LLM applications. Connect Mollie through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
Ask AI about this MCP Server for LangChain
The Mollie MCP Server for LangChain is a standout in the Money Moves category — giving your AI agent 7 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"mollie-alternative": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using Mollie, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* 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.
LangChain's ecosystem of 500+ components combines seamlessly with Mollie through native MCP adapters. Connect 7 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
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 LangChain 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 LangChain
When LangChain 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 payment on Mollie
Create a new payment
Get payment details on Mollie
Get details for a specific payment
List customer subscriptions on Mollie
List subscriptions for a customer
List customers on Mollie
List Mollie customers
List payment methods on Mollie
List available payment methods
List payments on Mollie
List Mollie payments
List refunds on Mollie
List all refunds
Connect Mollie to LangChain via MCP
Follow these steps to wire Mollie into LangChain. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install dependencies
pip install langchain langchain-mcp-adapters langgraph langchain-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
python agent.pyExplore tools
Why Use LangChain with the Mollie MCP Server
LangChain provides unique advantages when paired with Mollie through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Mollie MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across Mollie queries for multi-turn workflows
Mollie + LangChain Use Cases
Practical scenarios where LangChain combined with the Mollie MCP Server delivers measurable value.
RAG with live data: combine Mollie tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Mollie, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Mollie tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Mollie tool call, measure latency, and optimize your agent's performance
Example Prompts for Mollie in LangChain
Ready-to-use prompts you can give your LangChain 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 LangChain
Common issues when connecting Mollie to LangChain through Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersMollie + LangChain FAQ
Common questions about integrating Mollie MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
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