How to Use the Wati MCP in Vercel AI SDK

Q: How can I check Wati contact lists using Vercel AI SDK?

You use the listwhatsappcontacts tool. Your agent calls this, gets the list of all contacts in the Wati CRM, and streams that array to your client for display. It's fast because you're streaming results.

Q: What if I need to check broadcast campaigns with Wati using Vercel AI SDK?

You use listbroadcastcampaigns. Your agent calls this tool when the user needs an overview of past or active campaigns. The result streams directly into your UI, allowing you to build a dashboard that updates live.

Q: Is authentication handled easily with Wati and Vercel AI SDK?

Yes. Since the Vercel AI SDK supports an authProvider for OAuth, integrating with the Wati MCP Server is straightforward. You handle user permissions before your agent makes any API calls.

Q: How does Wati manage message templates when using Vercel AI SDK?

You access approved and pending templates via listwhatsapptemplates. Your agent uses this list to ensure that any template you try to send with the sendtemplatemessage tool is valid before execution.

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Connect Wati MCP to Vercel AI SDK

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Setup Wati with Vercel AI SDK

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Streaming WhatsApp History into your UI with Vercel AI SDK

The `get_whatsapp_chat_history` tool retrieves recent messages for any contact. With the Vercel AI SDK, you stream this history directly to your React or Next.js frontend. This means users see the conversation data appearing live, without a loading spinner. You'll use this pattern when building conversational interfaces. Instead of waiting for a full JSON response, your agent streams each message chunk as it arrives, making the application feel instant and snappy.

Managing Wati Contacts in Real-Time

Need to verify who you're talking to? The `get_whatsapp_contact_details` tool pulls profile info for a specific WhatsApp user. Pass this data into your Vercel AI SDK agent, and it can immediately decide on the next action—whether that’s sending a message or listing templates. This capability is perfect for client-side tools where immediate feedback matters. You get the contact's details first, then you pass them down the stream to keep the UI updated as your AI works.

Sending Messages via Vercel AI SDK

The MCP Server exposes two sending tools: `send_session_message` and `send_template_message`. Your agent can decide which one to use based on user input or campaign status. When you trigger these actions, the result streams back to your front end. This gives you total control over the user experience. You're not just sending a message; you're streaming the confirmation of that action into the UI, confirming the API call worked in real-time.

Setup guide

Set up Wati 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 Wati 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 Wati transactions",
});

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

Get your connection token →

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Common questions about Wati MCP in Vercel AI SDK

You use the `list_whatsapp_contacts` tool. Your agent calls this, gets the list of all contacts in the Wati CRM, and streams that array to your client for display. It's fast because you're streaming results.

This server handles WhatsApp contact details, chat history, and template metadata. The core data type is the Contact record itself, which includes phone numbers and profile information.

You use `list_broadcast_campaigns`. Your agent calls this tool when the user needs an overview of past or active campaigns. The result streams directly into your UI, allowing you to build a dashboard that updates live.

Yes. Since the Vercel AI SDK supports an `authProvider` for OAuth, integrating with the Wati MCP Server is straightforward. You handle user permissions before your agent makes any API calls.

You access approved and pending templates via `list_whatsapp_templates`. Your agent uses this list to ensure that any template you try to send with the `send_template_message` tool is valid before execution.

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