Mollie MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Mollie as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Mollie. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Mollie?"
)
print(response)
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 merchant account to your AI agent and take control of your payment workflows and e-commerce operations through natural conversation.
LlamaIndex agents combine Mollie tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the Mollie MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
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
Why Use LlamaIndex with the Mollie MCP Server
LlamaIndex provides unique advantages when paired with Mollie through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Mollie tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Mollie tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Mollie, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Mollie tools were called, what data was returned, and how it influenced the final answer
Mollie + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Mollie MCP Server delivers measurable value.
Hybrid search: combine Mollie real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Mollie to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Mollie for fresh data
Analytical workflows: chain Mollie queries with LlamaIndex's data connectors to build multi-source analytical reports
Mollie MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Mollie to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting Mollie to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpMollie + LlamaIndex FAQ
Common questions about integrating Mollie MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Mollie with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Mollie to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.