How to Use the WSLA (WhatsApp) MCP in Mastra AI

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

Yes. You expose the listwhatsapptemplates tool to your agent. The workflow can check these available types and decide which template to use next.

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Connect WSLA (WhatsApp) MCP to Mastra AI

Create your Vinkius account to connect WSLA (WhatsApp) to Mastra AI 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 Mastra AI

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Perplexity

Executing Core Text Messages

The system uses `send_whatsapp_text` to send a simple message when triggered. This is straightforward, but it's designed to be part of a larger workflow that handles retries. Mastra AI builds reliability into the process. If sending fails, the platform automatically retries the call with exponential backoff until successful.

Structured Template Delivery

You'll use `list_whatsapp_templates` to check which message formats are allowed before attempting delivery. Then, `send_whatsapp_template` executes the structured send. This workflow is ideal for mission-critical communications where failure handling must be guaranteed, like payment confirmations or account alerts.

Gathering Media Information

Need to check if a media item exists before proceeding? Call `get_whatsapp_media_details` first. This gives the workflow critical data points. This initial data retrieval step allows Mastra AI's built-in engine to make conditional decisions—for example, 'if media details are missing, then notify an admin.'

Setup guide

Set up WSLA (WhatsApp) MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All WSLA (WhatsApp) tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "wsla-whatsapp-mcp-client",
  servers: {
    "wsla-whatsapp-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "WSLA (WhatsApp) Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to WSLA (WhatsApp) tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent WSLA (WhatsApp) transactions"
);
console.log(result.text);

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Common questions about WSLA (WhatsApp) MCP in Mastra AI

You configure a multi-step workflow in the Mastra AI framework. The agent calls `send_whatsapp_text`, and if that fails, the engine automatically retries the send action.

Yes. You expose the `list_whatsapp_templates` tool to your agent. The workflow can check these available types and decide which template to use next.

Absolutely. You set up conditional branches. For example, if the initial `send_whatsapp_template` fails, your workflow can automatically switch to sending a fallback text message.

The MCP Server acts as the tool endpoint that Mastra AI calls. It allows your complex workflow to execute simple, reliable actions like sending a reaction or getting media details.

The server touches message content and media details. Mastra AI's strength is ensuring that the transmission and handling of these sensitive communications happen with guaranteed retries.

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