How to Use the Conekta MCP in LlamaIndex

Q: How do I index Conekta order histories into LlamaIndex?

You use listorders with the McpToolSpec to pull payment records into your index. LlamaIndex converts these order details into vector embeddings for semantic search.

Q: Can LlamaIndex query Conekta customer profiles in real-time?

Yes, the searchcustomerbyemail tool lets your LlamaIndex agent find active profiles instantly. It combines live API data with your indexed vector stores to answer customer queries.

Q: How does this MCP Server prevent hallucinations in LlamaIndex?

The server provides direct access to live data like getorder. Grounding your LlamaIndex agent in actual API responses prevents it from inventing transaction histories or payment statuses.

Index Mexican payment data into vector stores to query Conekta records directly from LlamaIndex.

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Connect Conekta MCP to LlamaIndex

Create your Vinkius account to connect Conekta 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 Conekta with LlamaIndex

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Index Mexican payment data using LlamaIndex

The `list_orders` tool retrieves your complete transaction history to build a searchable knowledge base within LlamaIndex. Instead of manually inspecting payment statuses, your agent indexes past transactions to answer complex financial queries. This integration turns raw Mexican transaction logs into searchable LlamaIndex vector embeddings. Your LlamaIndex agent queries this index to find patterns in sales volume or flag unpaid balances without hitting the live API repeatedly.

Run semantic search on Conekta profiles

The `search_customer_by_email` tool lets your agent locate specific profiles and index their payment history. By loading these profiles into your vector store, your agent performs semantic searches across your entire Mexican customer base. You initialize this using the McpToolSpec to expose Conekta customer data to your LlamaIndex FunctionAgent. The agent matches natural language queries with actual payment records, avoiding hallucinations by grounding answers in real Conekta data.

Build RAG pipelines with this MCP Server

The `list_subscription_plans` tool extracts Mexican recurring plans to ground your LlamaIndex sales agent's responses. By integrating this MCP Server with LlamaIndex, your agent references live subscription tiers during customer interactions. This RAG setup ensures your customer-facing agents never quote outdated pricing. The agent pulls active plan details directly from the API, indexes them, and answers billing questions with total accuracy.

Setup guide

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

You use `list_orders` with the McpToolSpec to pull payment records into your index. LlamaIndex converts these order details into vector embeddings for semantic search.

Yes, the `search_customer_by_email` tool lets your LlamaIndex agent find active profiles instantly. It combines live API data with your indexed vector stores to answer customer queries.

Install llama-index-tools-mcp and initialize BasicMCPClient with your Vinkius endpoint. Convert it using McpToolSpec, then pass the tools to your FunctionAgent.

The server provides direct access to live data like `get_order`. Grounding your LlamaIndex agent in actual API responses prevents it from inventing transaction histories or payment statuses.

All customer profiles and billing details are protected by an ephemeral, zero-trust MCP Server sandbox environment. Vinkius secures the API connection, ensuring your customer records never leak into public LLM training datasets.

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