Conekta MCP Server for LlamaIndex 8 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Conekta as an MCP tool provider through 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 Conekta. "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in Conekta?"
)
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 Conekta MCP Server
Integrate your AI assistant with Conekta, the leading online payment gateway in Mexico and Latin America. By providing seamless connectivity to your Conekta account, your conversational agent can instantly analyze transaction data, verify specific charges, and keep track of your core e-commerce metrics directly through natural language requests.
LlamaIndex agents combine Conekta tool responses with indexed documents for comprehensive, grounded answers. Connect 8 tools through 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
- Transaction Lookups — Instantly query the status of specific payments by providing a transaction ID or customer email.
- Sales Analysis — Ask for summaries of recent successful transactions, refunds, or chargebacks to keep track of store performance.
- Customer Management — Retrieve and review customer profiles and their associated payment history to provide faster support.
The Conekta 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 Conekta to LlamaIndex via MCP
Follow these steps to integrate the Conekta 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 Conekta
Why Use LlamaIndex with the Conekta MCP Server
LlamaIndex provides unique advantages when paired with Conekta through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Conekta tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Conekta tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Conekta, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Conekta tools were called, what data was returned, and how it influenced the final answer
Conekta + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Conekta MCP Server delivers measurable value.
Hybrid search: combine Conekta real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Conekta 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 Conekta for fresh data
Analytical workflows: chain Conekta queries with LlamaIndex's data connectors to build multi-source analytical reports
Conekta MCP Tools for LlamaIndex (8)
These 8 tools become available when you connect Conekta to LlamaIndex via MCP:
create_order
Requires customer name, email, phone, and at least one line item with name, unit_price (in cents), and quantity. Currency defaults to MXN. Create a new order in Conekta
get_customer
Returns contact info, payment sources, and order history. Retrieve detailed information about a specific customer
get_order
Returns charges, line items, customer info, and payment status. Retrieve detailed information about a specific order
list_customers
Retrieve a list of customer records from Conekta
list_events
Useful for debugging integrations. Retrieve a list of API events (webhook history)
list_orders
Use payment_status filter to narrow results. Supports limit for pagination. Retrieve a paginated list of orders from Conekta
list_subscription_plans
Retrieve a list of subscription plans in Conekta
search_customer_by_email
Returns matching customer profiles. Find a Conekta customer by their email address
Example Prompts for Conekta in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Conekta immediately.
"Check if the Conekta payment with ID 'ord_2nx...4kx' was successfully processed or declined."
"Summarize today's approved transactions and total revenue in MXN."
"List the last 5 chargebacks or disputed claims in our account."
Troubleshooting Conekta MCP Server with LlamaIndex
Common issues when connecting Conekta to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpConekta + LlamaIndex FAQ
Common questions about integrating Conekta 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 Conekta 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 Conekta to LlamaIndex
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.