How do I securely obtain my Conekta Private API Key?

Log in to your Conekta dashboard as an administrator. In the left sidebar, click on 'Developers' (Desarrolladores), then navigate to 'API Keys' (Llaves API). Locate the 'Private Key' (Llave Privada) section—you may need to enter your password to reveal it. Copy this key and paste it into the secure input field below to connect the agent.

Can the AI agent create new charges or issue refunds directly?

No. This integration operates strictly in read-only mode to guarantee financial security. The conversational agent can query and extract data regarding transactions, customers, and overall payments, but it cannot authorize new charges or initiate refunds, protecting your account from unintended financial actions.

What kind of data can I ask the agent to retrieve from Conekta?

You can ask the agent to check the exact status of a specific payment ID, verify whether a charge was approved or declined, list recent successful orders, or summarize the daily transaction volume and associated processing fees.

Conekta MCP Server for LangChain 8 tools — connect in under 2 minutes

Name: Conekta
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 8 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Conekta through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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 langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "conekta": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Conekta, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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.

LangChain's ecosystem of 500+ components combines seamlessly with Conekta through native MCP adapters. Connect 8 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

Follow these steps to integrate the Conekta MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 8 tools from Conekta via MCP

Why Use LangChain with the Conekta MCP Server

LangChain provides unique advantages when paired with Conekta through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Conekta MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Conekta queries for multi-turn workflows

Conekta + LangChain Use Cases

Practical scenarios where LangChain combined with the Conekta MCP Server delivers measurable value.

RAG with live data: combine Conekta tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Conekta, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Conekta tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Conekta tool call, measure latency, and optimize your agent's performance

Conekta MCP Tools for LangChain (8)

These 8 tools become available when you connect Conekta to LangChain 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 LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

Common issues when connecting Conekta to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Conekta + LangChain FAQ

Common questions about integrating Conekta MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.