How to Use the Checkout.com MCP in LlamaIndex

Q: Can LlamaIndex search my Checkout.com payment details?

Your agent calls getpaymentdetails to extract billing logic properties. Those properties get embedded into your vector store. You can then query that specific transaction history anytime.

Q: Does the Checkout.com MCP Server work with LlamaIndex data filters?

You can use the allowedtools parameter to restrict agent access. If you only want an agent to read data, give it getinstrument and block createinstrument.

Index your Checkout.com payment history with LlamaIndex. Query actual transaction data and vaulted instruments through your RAG pipeline and this MCP Server.

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Connect Checkout.com MCP to LlamaIndex

Create your Vinkius account to connect Checkout.com 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 Checkout.com with LlamaIndex

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Index Live Payment Actions

The `get_payment_actions` tool pulls structured rules and gateway states straight from Checkout.com. LlamaIndex takes those raw JSON arrays and immediately embeds them into your vector store. Your knowledge base now contains actual, up-to-the-minute billing logic. Querying past sessions actually works. Instead of guessing why a charge failed last Tuesday, your RAG application retrieves the exact gateway response. The agent reads the embedded data and gives you an answer grounded in reality, entirely skipping hallucinations.

Search Vaulted Instruments via MCP Server

Fetch active arrays across your customer base using the `get_instrument` tool. LlamaIndex indexes these Vault limits and churn flags. You can ask your agent how many active Visa cards are currently provisioned for a specific billing tier. Updating records happens through the same interface. The `update_instrument` tool modifies cloud logging and Vault limits. After the update, your RAG system syncs the new state, keeping your searchable index perfectly aligned with the live gateway.

Grounded Refund Verification

Trigger the `refund_payment` tool to push cash back to the originating network. LlamaIndex logs the exact clawback logic and transaction ID returned by the API. Your searchable history updates instantly. Customer support queries become trivial. A rep asks the agent if an order was refunded. The system searches the vector database, finds the exact tool output from the MCP server, and confirms the status using hard data.

Setup guide

Set up Checkout.com 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 Checkout.com 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 Checkout.com tools.",
)
response = await agent.run("List recent Checkout.com 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 Checkout.com. 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 Checkout.com MCP in LlamaIndex

Install llama-index-tools-mcp and set up a BasicMCPClient. Wrap it in McpToolSpec and call to_tool_list_async(). Pass that list directly to your FunctionAgent.

Your agent calls get_payment_details to extract billing logic properties. Those properties get embedded into your vector store. You can then query that specific transaction history anytime.

You can use the allowed_tools parameter to restrict agent access. If you only want an agent to read data, give it get_instrument and block create_instrument.

API responses disappear after the call finishes. LlamaIndex turns those responses into a permanent, searchable knowledge base. Your agent answers questions based on historical gateway data.

The MCP server runs inside a zero-trust environment. LlamaIndex only receives the masked JSON payloads and token references returned by the API. No raw PANs ever enter your vector store or hit the indexing engine.

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