How to Use the Telebroad MCP in Mastra AI

Build resilient, complex telephony workflows with Telebroad using mastra-ai's failure handling.

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Connect Telebroad MCP to Mastra AI

Create your Vinkius account to connect Telebroad to Mastra AI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Telebroad with Mastra AI

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Claude

Perplexity

Orchestrate Call Management Logic

You can build multi-step calling logic that handles failures. For example, if the initial call fails, your workflow engine automatically retries using `send_call`. The MCP Server manages this complex state machine for you. Furthermore, if a critical connection is lost mid-operation, you'll use the built-in retry mechanism to attempt recovery or gracefully fail over, minimizing operational downtime.

Multi-Step Messaging Workflows

The framework handles complex messaging sequences. If sending an SMS fails due to a temporary network issue, your workflow can automatically wait and then retry using `send_sms`. This is crucial for reliable communications. It also lets you list all potential lines via `list_sms_lines` before attempting mass communication, ensuring you always have capacity.

Directory & Status Checks

The workflow can check status and directory information in sequence. First, it calls `get_profile` to verify the user's identity within the current context. Then, if needed, it uses `list_phone_destinations` to get a validated extension list. This allows you to build robust pre-call checks that don't fail on minor API hiccups.

Setup guide

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

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

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

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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 Telebroad. 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 Telebroad MCP in Mastra AI

The agent framework manages state and retries automatically. If a `send_call` fails due to transient issues, the workflow engine will retry the action using exponential backoff until it succeeds or hits a defined limit.

Yes. You can build parallel workflows that send both SMS and faxes. The system handles calling `send_sms` and then separately invoking `send_fax`, treating them as two distinct, yet connected, tasks.

The workflow will trap the failure. You can write logic to execute an alternative action—like sending an SMS notification instead of calling—if the primary communication method fails.

The framework treats messaging logs as a resource. You can use `list_sms_conversations` to gather all relevant threads, which then feeds into the main workflow for review.

It touches communication metadata: call logs and SMS conversation records. Because of this, you must ensure your workflows handle potential PII found in message content or call details securely.

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