How to Use the Mambu MCP in Vercel AI SDK

Stream real-time banking data from Mambu directly into your Vercel AI SDK frontends for instant, reactive user experiences.

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Connect Mambu MCP to Vercel AI SDK

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

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Claude

Perplexity

Live loan and deposit monitoring

Feed live account status into your interface using `get_loan_account` and `get_deposit_account`. Since you are using the Vercel AI SDK, these updates stream directly into your UI components without blocking the main thread. Your users see their financial data update as the AI fetches it. You avoid stale UI states by piping these tool outputs straight through your edge functions.

Automated client data retrieval

Pull specific client profiles into your chat context with `get_client`. This prevents the AI from guessing account details during a conversation. Your application logic stays clean because the Vercel AI SDK handles the tool execution lifecycle. Simply map the tool results to your state management and let the UI react.

Real-time transaction visibility

Track recent account activity by calling `list_transactions` during a user session. You get the latest ledger entries pushed straight to your frontend state. This setup works perfectly for building dashboards that require immediate data visualization. You handle the auth, and the MCP server handles the data ingestion.

Setup guide

Set up Mambu 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 Mambu 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 Mambu 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 Mambu. 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.

Why Choose Vinkius

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Common questions about Mambu MCP in Vercel AI SDK

You handle authentication at the transport layer before the server processes requests. Use your environment variables to pass the required tokens securely to the MCP server.

Yes, but keep an eye on your Mambu API rate limits. Cache your responses in your edge layer if you find yourself hitting those thresholds too often.

Absolutely. It transmits data in a format that your streamText implementation interprets natively. You get the performance benefits of streaming without custom parsing.

The data lives in your application's state or local database once the tool returns it. Your agent acts as the bridge between the banking platform and your UI.

Your client data—specifically PII and account balances—never touches our servers. The connection is direct between your environment and the bank, ensuring your user records remain isolated.

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