How to Use the AfterLogic Aurora MCP in Mastra AI

Q: How do I configure Mastra AI to use AfterLogic Aurora?

Run npm install @mastra/mcp@latest. Create a new MCPClient instance and pass your Vinkius endpoint URL. Mastra automatically figures out if it should use SSE or Streamable HTTP.

Q: How do I pass AfterLogic Aurora tools into a Mastra AI agent?

Call mcpClient.listTools() on your initialized client. Spread that array directly into your Agent configuration. The workflow engine handles the rest.

Build reliable email automation workflows with Mastra AI and AfterLogic Aurora.

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Connect AfterLogic Aurora MCP to Mastra AI

Create your Vinkius account to connect AfterLogic Aurora 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 AfterLogic Aurora with Mastra AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Automate email delivery resiliently.

Handling AfterLogic Aurora API timeouts gracefully is built right into Mastra AI. Network requests fail constantly in production environments. The framework wraps your outbound calls in automatic retries with exponential backoff. When your agent executes `send_email`, the workflow engine monitors the HTTP response. If the web API stumbles, Mastra pauses and tries again later. You stop writing custom error handling logic.

Conditional inbox routing.

Routing incoming AfterLogic Aurora messages based on content saves your support desk hours. You can build a workflow that reads incoming mail and makes decisions dynamically. The agent decides where the thread belongs without human input. The workflow triggers `list_messages` targeting a specific directory from `list_folders`. If the AI detects a billing issue, it branches the logic to notify finance. Otherwise, it files it under general support.

Safe admin operations via this MCP Server.

Auditing AfterLogic Aurora admin operations requires a safety net. Handing an AI the keys to your domain mappings sounds terrifying. This MCP Server lets you inject approval gates into the process. Turn on `requireToolApproval` for your sensitive endpoints. When the agent attempts to run `check_account_exists` or `list_domains`, execution pauses. An administrator clicks approve, and the workflow continues safely.

Setup guide

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

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

const result = await agent.generate(
  "List recent AfterLogic Aurora 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 AfterLogic Aurora. 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 AfterLogic Aurora MCP in Mastra AI

Run `npm install @mastra/mcp@latest`. Create a new `MCPClient` instance and pass your Vinkius endpoint URL. Mastra automatically figures out if it should use SSE or Streamable HTTP.

It can, provided you give it admin credentials. The agent calls the `check_account_exists` tool. You can wrap this in conditional logic to branch your onboarding workflow.

Call `mcpClient.listTools()` on your initialized client. Spread that array directly into your Agent configuration. The workflow engine handles the rest.

The built-in workflow engine manages those failures. If the API rejects a request, the framework catches the error and applies exponential backoff before trying again.

Your outbound drafts and incoming folder hierarchies never touch persistent storage. The connection runs zero-trust, meaning it authenticates, executes `send_email`, and terminates. No logs keep your message bodies.

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