How to Use the Asaas MCP in Vercel AI SDK

Q: Can I stream Asaas billing lists directly to React components using Vercel AI SDK?

Yes. By passing listpayments as an MCP tool to the SDK, the system streams raw payment states directly to your UI. You can map these payments to custom React components without waiting for the full payload to resolve.

Q: How does the Vercel AI SDK handle failed Asaas payment attempts?

The SDK captures the error directly from the failed createpayment tool call. Your agent reads the error, explains the payment failure to the user, and can immediately retry the operation with corrected billing details.

Pipe live Brazilian payment events directly into your Next.js UI using the Vercel AI SDK and this MCP Server.

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Connect Asaas MCP to Vercel AI SDK

Create your Vinkius account to connect Asaas to Vercel AI SDK 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 Asaas with Vercel AI SDK

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Live React registration with this MCP Server

Your edge-rendered UI calls `create_customer` to register Brazilian clients instantly without loading spinners. By rendering the output state step-by-step, your users get immediate feedback on their signup status. Combining the Vercel AI SDK with our managed endpoint lets your agent read the live output state to handle validation errors on the fly. You get clean Asaas customer records without writing tedious form-handling boilerplate.

Stream payment links directly to your Vercel AI SDK chat

When a customer asks your chatbot to pay an invoice, the agent invokes `create_payment` to render the charge status in real-time. The user sees the Pix copy-paste key or credit card form appear right inside the message bubble. You feed `list_payments` directly into your streaming components to show active bills. Your customers can track their outstanding Brazilian invoices through an interactive chat interface that updates as payments clear.

Render live Asaas balances in your frontend

Your edge-rendered chatbot calls `get_balance` and `list_subscriptions` to display real-time cash flow and recurring plan metrics directly to your users. It keeps your Next.js app fast because the execution happens on Vinkius sandboxes. The Vercel AI SDK receives the structured MCP tool output and maps it to your custom dashboard components immediately. This approach bypasses heavy backend weight and database polling.

Setup guide

Set up Asaas MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all Asaas tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent Asaas transactions",
});

console.log(text);
await mcpClient.close();

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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 Asaas. 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 Asaas MCP in Vercel AI SDK

You do not need to manage complex Brazilian API keys in your frontend code. Vinkius handles the credentials securely, giving you a single endpoint token to pass when initializing the client in your edge route.

Yes. By passing `list_payments` as an MCP tool to the SDK, the system streams raw payment states directly to your UI. You can map these payments to custom React components without waiting for the full payload to resolve.

The SDK captures the error directly from the failed `create_payment` tool call. Your agent reads the error, explains the payment failure to the user, and can immediately retry the operation with corrected billing details.

Yes. The Vercel AI SDK configuration is fully edge-compatible. Because Vinkius runs the server in an isolated sandbox, your edge functions stay lightweight and secure.

Vinkius runs the server in an ephemeral sandbox that never stores your financial transactions or customer PI. All payload data passing through `create_customer` and `list_transfers` goes directly to the Brazilian gateway, keeping your compliance scope minimal.

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