Checkout.com 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 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.
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 Checkout.com. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Checkout.com?"
)
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 Checkout.com MCP Server
Connect your Checkout.com account to any AI agent and take full control of your payment workflows through natural conversation.
LlamaIndex agents combine Checkout.com 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
- Payments — Request, capture, void, and refund payments with support for various currencies and sources
- Vaulting (Instruments) — Securely create, list, update, and delete payment instruments (cards) in the Checkout.com Vault
- Payment Actions — Track every action taken on a payment to understand authorization successes and failures
- Analytics & History — Audit payment statuses and details directly from your workspace
The Checkout.com 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 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 10 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 (10)
These 10 tools become available when you connect Checkout.com to LlamaIndex via MCP:
capture_payment
/captures` locking an authorized transaction converting it to native settled limits. Retrieve the exact structural matching verifying Capture processing
create_instrument
Provision a highly-available JSON Payload generating hard Customer bindings
delete_instrument
Irreversibly vaporize explicit validations extracting rich Churn flags
get_instrument
Identify precise active arrays spanning native Vault logic
get_payment_actions
Enumerate explicitly attached structured rules exporting Gateway state
get_payment_details
com nodes. Perform structural extraction of properties driving active Billing logic
refund_payment
/refunds` moving hard cash back exactly to the originating Visa/MC network. Dispatch an automated validation check routing explicit Clawback logic
request_payment
Identify bounded CRM records inside the Headless Checkout.com Gateway
update_instrument
Retrieve explicit Cloud logging tracing explicit Vault limits
void_payment
/voids` dropping limits before a capture closes cutting out heavy gateway fees. Inspect deep internal arrays mitigating specific Plan Math
Example Prompts for Checkout.com in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Checkout.com immediately.
"Refund payment pay_123 for $50.00"
"Show me why payment pay_456 failed"
"Vault this instrument ID src_789 and update the holder name to 'John Doe'"
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
pip install llama-index-tools-mcpCheckout.com + LlamaIndex FAQ
Common questions about integrating Checkout.com 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 Checkout.com 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 Checkout.com to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.