How to Use the Dexatel MCP in Mastra AI

Build resilient SMS workflows and automated retry loops with Mastra AI and Dexatel.

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Connect Dexatel MCP to Mastra AI

Create your Vinkius account to connect Dexatel 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 Dexatel with Mastra AI

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Claude

Perplexity

Automate fallback logic with this MCP Server

Running `list_failed_sms_deliveries` on a schedule lets your Mastra workflow anticipate and handle dropped texts. Messaging pipelines break. Carriers reject texts, numbers bounce, and accounts run out of funds. By connecting the Dexatel MCP Server to your framework, you catch these failures immediately. You configure the workflow to branch automatically when it finds a bounced message. The agent checks `get_account_balance_metadata` to see if funds are low, or alerts an admin if a specific carrier blocks your traffic.

Orchestrate complex campaign rollouts

Your Mastra workflow can pull approved copy using `list_sms_templates` and sequence an outbound batch. Sending a blast isn't just about hitting an endpoint. The agent grabs the target audience via `list_messaging_contacts` and executes everything within a defined, retry-capable pipeline. API limits won't break your pipeline. Mastra provides built-in exponential backoff, meaning if `send_sms_message` hits a throttle, the system waits and tries again. You get reliable delivery without writing custom retry wrappers.

Keep human oversight on outbound texts

Before firing off a blast, your agent can verify sender details using `list_authorized_sender_ids`. Nobody wants an autonomous script sending unapproved messages to thousands of customers. Mastra AI lets you enforce requireToolApproval on destructive actions. Your agent drafts the texts, but a human clicks confirm before anything goes out. This guarantees the blast comes from the correct regional number. You maintain total control over the final execution.

Setup guide

Set up Dexatel 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 Dexatel 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: "dexatel-mcp-client",
  servers: {
    "dexatel-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

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

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Why Choose Vinkius

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Common questions about Dexatel MCP in Mastra AI

Install the MCPClient package and instantiate it with your server URL. Call mcpClient.listTools() to inject the messaging capabilities directly into your workflow.

Yes. You build a branch that triggers if a send fails. The workflow engine applies exponential backoff and attempts the delivery again based on your configured rules.

Mastra handles the backoff natively. It pauses the execution state and retries the tool call later, preventing your campaign from crashing halfway through.

Absolutely. Flag the send tool with requireToolApproval. The workflow halts, notifies you, and waits for manual sign-off before dispatching the text.

Message templates and SMS contents are processed entirely in memory during execution. The sandbox environment is ephemeral. Once the Mastra pipeline completes, the instance terminates, leaving no residual logs of your private communications.

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