How to Use the Efí Pay (Gerencianet) MCP in Mastra AI

Build resilient payment workflows in Mastra AI using the Efí Pay (Gerencianet) MCP Server for automated financial operations.

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Connect Efí Pay (Gerencianet) MCP to Mastra AI

Create your Vinkius account to connect Efí Pay (Gerencianet) to Mastra AI 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 Efí Pay (Gerencianet) with Mastra AI

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Perplexity

Automated Payment Retry Logic

Define complex agents in Mastra AI that use `efi_create_pix_charge` with built-in conditional branching. If a charge fails, your workflow engine automatically catches the error and triggers a fallback method. This handles the heavy lifting of payment failures. Your agents manage the entire lifecycle of a transaction without you needing to write manual error-handling loops for every possible API hiccup.

Multi-Step Financial Workflows

Chain `efi_list_boletos` with `efi_get_statement` to build automated reconciliation pipelines. Mastra AI agents execute these steps sequentially or in parallel, depending on your business rules. It turns your accounting process into a repeatable, code-defined workflow. You get a clear audit trail of every operation performed by the agent against your Efí Pay (Gerencianet) account.

Human-in-the-loop Approvals

Use `requireToolApproval` to pause execution before your agent calls `efi_send_pix`. This ensures you verify every outgoing transfer before the agent completes the transaction. It gives you full control over high-stakes financial operations. You define the thresholds, and the agent respects them, only executing the final transaction after your manual sign-off.

Setup guide

Set up Efí Pay (Gerencianet) MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All Efí Pay (Gerencianet) tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "efi-pay-gerencianet-mcp-client",
  servers: {
    "efi-pay-gerencianet-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Efí Pay (Gerencianet) Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Efí Pay (Gerencianet) tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Efí Pay (Gerencianet) transactions"
);
console.log(result.text);

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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 Efí Pay. 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 Efí Pay (Gerencianet) MCP in Mastra AI

You register the server in your agent configuration. Mastra AI automatically detects the tools, allowing you to include them in any step of your agent's execution sequence.

Yes. You can configure retries and backoff policies directly within the agent definition. If an API call fails, the framework manages the recovery attempt.

It provides a stable interface for all account operations. By utilizing the framework's workflow engine, you ensure that every tool call is logged and auditable.

All account statements and transaction history are processed within an isolated memory space. The agent only interacts with the raw API data provided during the execution of a tool.

You use environment variables to inject credentials securely into the server. The framework isolates these secrets from your agent logic, preventing accidental exposure.

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