How to Use the Gallabox MCP in Vercel AI SDK

Q: How do I connect Vercel AI SDK to Gallabox?

Install @ai-sdk/mcp and instantiate the client using createMCPClient. You pass your Gallabox MCP Server endpoint URL into the HTTP transport configuration. Call mcpClient.tools() and feed the result into streamText.

Q: Can Vercel AI SDK stream WhatsApp templates from Gallabox?

Yes. Your agent calls listmessagetemplates to fetch available options. The SDK streams the template names and variables back to your Next.js UI so the user can select the right one.

Build live WhatsApp chat interfaces in React and Next.js using the Gallabox MCP Server.

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Connect Gallabox MCP to Vercel AI SDK

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

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Stream chats to Vercel AI SDK

The `list_thread_messages` tool pulls raw WhatsApp conversation history directly into your Vercel AI SDK application. You don't wait for a massive JSON payload to resolve. The text streams straight into your React or Next.js frontend while the agent reads the thread. You pair this with `list_active_chats` to build live inbox views. When a customer replies, your edge function fetches the delta and pushes it to the UI via the MCP standard. Users watch the AI analyze the conversation context in real time.

Dispatch templates and replies

The `send_whatsapp_template` tool dispatches pre-approved Meta templates to your contacts. Your agent selects the exact template ID based on user input and fires off the request. If the conversation requires a custom response, the agent switches to `send_whatsapp_text`. This means your application handles both structured notifications and free-form support. You hook the tool results into the Vercel AI SDK stream. The user sees a confirmation badge appear the millisecond the message hits the WhatsApp API network.

Query contacts and teams

The `get_contact_details` tool fetches metadata for any phone number interacting with your system. Your agent grabs the contact ID, checks their profile, and routes the data to your frontend components. You instantly display customer names and past interaction tags. If the AI determines a human needs to step in, it calls `list_support_teams`. The agent identifies the correct internal Gallabox queue. It passes that team ID back to your application logic to trigger an immediate handoff through the MCP Server.

Setup guide

Set up Gallabox 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 Gallabox 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 Gallabox 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 Gallabox. 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 Gallabox MCP in Vercel AI SDK

Install `@ai-sdk/mcp` and instantiate the client using `createMCPClient`. You pass your Gallabox MCP Server endpoint URL into the HTTP transport configuration. Call `mcpClient.tools()` and feed the result into `streamText`.

Yes. Your agent calls `list_message_templates` to fetch available options. The SDK streams the template names and variables back to your Next.js UI so the user can select the right one.

You can use React, Vue, Svelte, or solid.js. The SDK handles the streaming state management on the client side while your backend communicates with the tools.

You manage the Vinkius endpoint token on the server side. Pass the token in the `authProvider` block when initializing your HTTP transport. Never expose this token to the browser.

The server processes phone numbers and raw message text strictly in memory. The V8 Isolate Sandbox destroys the environment the moment the request finishes. No thread histories or contact details persist on the infrastructure.

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