How to Use the WSLA (WhatsApp) MCP in Vercel AI SDK

Q: How do I use WSLA (WhatsApp) with Vercel AI SDK to send messages?

You call sendwhatsapptext through your streaming client. The agent sends the text, and because you're using the Vercel AI SDK, the user sees that message appear in real-time on the front end.

Q: Can I list templates for WSLA (WhatsApp) with Vercel AI SDK?

Yep. You run listwhatsapptemplates and the result streams back to your UI, allowing you to display available template names immediately after calling the MCP Server.

Q: What's the process for sending a reaction via WSLA (WhatsApp) with Vercel AI SDK?

You invoke sendwhatsappreaction. This is a simple action, but it requires knowing which message and what emoji you want to react with. The result streams back instantly.

Send WhatsApp messages and react in real-time using the Vercel AI SDK.

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Connect WSLA (WhatsApp) MCP to Vercel AI SDK

Create your Vinkius account to connect WSLA (WhatsApp) 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 WSLA (WhatsApp) with Vercel AI SDK

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Real-Time Messaging Updates

Need to send a simple message? You call `send_whatsapp_text` directly. The result streams into your UI, so the user sees the text appear live—no loading spinners needed. This capability is perfect for chat interfaces where the user expects immediate feedback from your agent. It handles basic text delivery via the MCP Server.

Managing Message Templates

Before sending something structured, check `list_whatsapp_templates` to see what types of messages are available through Meta's system. Then, you use `send_whatsapp_template` to fire off a pre-approved message. This ensures your agent only sends compliant messaging formats, which is critical for automated business communication. It makes sure the AI client works with valid parameters.

Observing and Reacting to Media

When you need to know what media was sent or check its status, use `get_whatsapp_media_details`. This gets specific metadata about an image or video that came through. If the conversation warrants a quick acknowledgement, call `send_whatsapp_reaction`. It's a small action but it keeps the user engaged and feels natural in the chat flow. The MCP Server manages these actions.

Setup guide

Set up WSLA (WhatsApp) 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 WSLA (WhatsApp) 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 WSLA (WhatsApp) 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 WSLA (WhatsApp). 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 WSLA (WhatsApp) MCP in Vercel AI SDK

You call `send_whatsapp_text` through your streaming client. The agent sends the text, and because you're using the Vercel AI SDK, the user sees that message appear in real-time on the front end.

Yep. You run `list_whatsapp_templates` and the result streams back to your UI, allowing you to display available template names immediately after calling the MCP Server.

You invoke `send_whatsapp_reaction`. This is a simple action, but it requires knowing which message and what emoji you want to react with. The result streams back instantly.

The Vercel AI SDK is built for streaming, so while it manages sequential tool calls well, it focuses on displaying real-time data results rather than complex internal workflow branching.

The server handles message content and media details. You should assume that any information passed to `send_whatsapp_text` or retrieved via `get_whatsapp_media_details` is sensitive communication data.

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