How to Use the MiiTel MCP in Mastra AI

Q: Can Mastra AI automate MiiTel call analysis?

Absolutely. You can write a workflow that loops through listcalls, processes the details, and stores the results in your database. It runs autonomously based on your logic.

Q: Is my MiiTel contact data private when using Mastra AI?

The server only exposes the specific records you query via listsyncedcontacts. No data is stored in the agent's memory beyond the current execution context.

Build automated sales coaching workflows with MiiTel and Mastra AI.

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Connect MiiTel MCP to Mastra AI

Create your Vinkius account to connect MiiTel 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 MiiTel with Mastra AI

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Automated Call Review Pipelines

Set up a Mastra agent to trigger `list_calls` on a schedule. If the sentiment score drops below your threshold, the workflow kicks off a review process. You handle the entire sequence in code. It catches problematic calls before a manager even has to look at the dashboard.

Conditional Meeting Follow-ups

Use `get_meeting_details` to check for specific keywords or outcomes. Your Mastra workflow can branch based on what happened during the call. If the meeting status indicates a follow-up is needed, the agent updates your CRM. It keeps the sales team moving without manual entry.

Team Performance Monitoring

Map your team's output by calling `list_miitel_users` alongside your call data. You can now build logic that flags reps who need extra support. The agent runs these checks in the background. It ensures that coaching is based on actual performance data rather than gut feeling.

Setup guide

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

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

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

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Common questions about MiiTel MCP in Mastra AI

You define the MiiTel server in your client config and spread the tools into your agent definition. Mastra handles the tool discovery and execution automatically.

Absolutely. You can write a workflow that loops through `list_calls`, processes the details, and stores the results in your database. It runs autonomously based on your logic.

Yes. You can mark specific tools as requiring approval. The agent will pause and ask a human to verify the action before it proceeds with the MiiTel request.

Mastra provides built-in retry logic. If the server hits a rate limit, the workflow waits and tries again, keeping your coaching pipeline running.

The server only exposes the specific records you query via `list_synced_contacts`. No data is stored in the agent's memory beyond the current execution context.

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