How to Use the Adyen MCP in LlamaIndex

Turn your Adyen MCP Server data into a semantic knowledge base. Let LlamaIndex query live payment data and execute refunds through natural language.

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Connect Adyen MCP to LlamaIndex

Create your Vinkius account to connect Adyen to LlamaIndex 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 Adyen with LlamaIndex

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Index live Adyen MCP Server transactions

The `get_payment_details` tool pulls 16-digit PSP references and turns them into vector embeddings. Your LlamaIndex application fetches the technical authorization metadata and immediately adds it to your searchable index. Support teams ask questions about past transactions and get answers grounded in live API data. Semantic search reads the exact capture status instead of guessing what happened to a customer's order.

Map merchant configurations into RAG

Calling `list_merchants` allows your data pipeline to index every active account across your global profile. The system maps out regional IDs and stores them as searchable nodes. You then run `get_merchant_details` to pull the technical status for each specific account. A FunctionAgent checks this indexed configuration before attempting to route any new payments.

Trigger refunds from semantic queries

A LlamaIndex FunctionAgent uses `refund_payment` to return funds directly from a chat interface. It double-checks the indexed payment amount and requires the original PSP reference before processing the request. Agents combine RAG context with active tool execution. They find the transaction in your vector store, verify the capture status, and execute the return in one fluid motion.

Setup guide

Set up Adyen MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Adyen MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Adyen tools.",
)
response = await agent.run("List recent Adyen data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Adyen. 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 Adyen MCP in LlamaIndex

Install llama-index-tools-mcp and initialize a basic client. Pass the resulting tools directly to your FunctionAgent.

Yes. The agent fetches transaction metadata and indexes it for semantic search alongside your other documents.

You instruct the FunctionAgent to calculate the specific amount based on the indexed order data before calling the refund tool.

No. Your LlamaIndex pipeline queries the active configuration directly using the active connection.

We run the MCP Server in an ephemeral V8 sandbox that handles authentication securely. LlamaIndex only receives the specific technical configurations and PSP references you explicitly query, ensuring zero-trust data access.

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