Can I process a refund for a payment ID through the agent?

Yes! Use the `refund_checkout_payment` tool with the payment ID. You can also specify an optional amount in minor units for a partial refund. The agent will trigger the refund process in Checkout.com immediately.

How do I see the full history of actions for a payment?

Use the `list_payment_actions` tool with the unique payment ID. Your agent will fetch all lifecycle events, such as Authorization, Capture, and Refund, along with their timestamps.

Where do I find my API Prefix?

The API Prefix is the first 8 characters of your client_id (excluding the cli_ prefix). You can also find it in your Checkout.com Hub under Developers -> API Keys.

Checkout.com MCP Server for LlamaIndex 8 tools — connect in under 2 minutes

Name: Checkout.com
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 8 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Checkout.com as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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 Checkout.com. "
            "You have 8 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Checkout.com?"
    )
    print(response)

asyncio.run(main())

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* 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 Checkout.com MCP Server

Connect your Checkout.com account to any AI agent and take full control of your global payment operations through natural conversation. Streamline how you manage transactions across 150+ currencies.

LlamaIndex agents combine Checkout.com tool responses with indexed documents for comprehensive, grounded answers. Connect 8 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

Unified Payment Oversight — List and retrieve details for all payments processed through the Unified API natively
Mutable Operations — Refund, capture, or void payments directly through secure conversational commands flawlessly
Action Auditing — List all lifecycle actions for any specific payment to track its history securely
Connectivity Monitoring — List and review configured webhooks to ensure your integration is running flawlessly
System Metadata — Retrieve core account information and user settings directly within your workspace flawlessly
minor unit Handling — Work with precise financial amounts in minor units for high-accuracy transaction management

The Checkout.com MCP Server exposes 8 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 Checkout.com to LlamaIndex via MCP

Follow these steps to integrate the Checkout.com 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 8 tools from Checkout.com

Why Use LlamaIndex with the Checkout.com MCP Server

LlamaIndex provides unique advantages when paired with Checkout.com through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Checkout.com tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Checkout.com tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Checkout.com, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Checkout.com tools were called, what data was returned, and how it influenced the final answer

Checkout.com + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Checkout.com MCP Server delivers measurable value.

Hybrid search: combine Checkout.com real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Checkout.com 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 Checkout.com for fresh data

Analytical workflows: chain Checkout.com queries with LlamaIndex's data connectors to build multi-source analytical reports

Checkout.com MCP Tools for LlamaIndex (8)

These 8 tools become available when you connect Checkout.com to LlamaIndex via MCP:

capture_checkout_payment

Capture an authorized payment

get_checkout_account_info

Retrieve core account and user information

get_payment_details

Get detailed information for a specific payment

list_checkout_payments

List recent payments

list_checkout_webhooks

List configured webhooks

list_payment_actions

List all lifecycle actions for a specific payment

refund_checkout_payment

Refund a captured payment

void_checkout_payment

Void an authorized payment

Example Prompts for Checkout.com in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Checkout.com immediately.

"Show me my last 5 payments in Checkout.com."

"What happened to payment ID 'pay_123456'?"

"Refund payment pay_789 for $10.50."

Troubleshooting Checkout.com MCP Server with LlamaIndex

Common issues when connecting Checkout.com to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Checkout.com + LlamaIndex FAQ

Common questions about integrating Checkout.com MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Checkout.com tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.