How to Use the Mailify (Sarbacane) MCP in Mastra AI

Build resilient marketing workflows in Mastra AI using the Mailify (Sarbacane) MCP Server tools.

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Connect Mailify (Sarbacane) MCP to Mastra AI

Create your Vinkius account to connect Mailify (Sarbacane) 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 Mailify (Sarbacane) with Mastra AI

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Automated list maintenance for Mastra AI

Create conditional workflows that trigger `delete_book_contact` when a user unsubscribes. You can set up automatic retries if the network drops. Use `list_book_contacts` as a data source for your agent's decision logic. If a contact is missing, the agent triggers an add operation automatically.

Workflow-driven campaign monitoring

Chain `get_campaign_details` into your Mastra AI agents to monitor launch status. You can branch your workflow based on the output of these tools. If performance metrics from `get_campaign_performance` dip below your threshold, tell your agent to alert the team. It happens without manual intervention.

Reliable MCP Server execution

Integrate the Mailify (Sarbacane) toolset into your Mastra AI agent definition. The framework handles the tool calls and ensures each operation finishes correctly. You gain a complete view of your marketing state by pulling `list_email_campaigns` into your agent's memory. This allows for long-running processes that stay accurate.

Setup guide

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

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

const result = await agent.generate(
  "List recent Mailify (Sarbacane) 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 Mailify (Sarbacane). 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 Mailify (Sarbacane) MCP in Mastra AI

Define the Mailify (Sarbacane) MCP Server in your Mastra AI config file. You can then add the tools to your agent and write logic to handle the response from `add_contact_to_book`.

Yes, the Mastra AI framework supports exponential backoff. If a request like `update_book_contact` fails, the system handles the retry automatically.

Absolutely. You can import the MCP Server directly and call `list_address_books` within your agent's execution loop.

You manage them through the Vinkius endpoint. Your agent only sees the tools you explicitly expose.

The server treats subscriber email addresses as restricted data. Every interaction via Mastra AI is isolated within an ephemeral environment that clears after each execution.

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