How to Use the Trigger.dev (Background Tasks & Jobs) MCP in Mastra AI

Q: How do I manage job status using Trigger.dev (Background Tasks & Jobs) with Mastra AI?

You use getrun to check the live status of a background task within your multi-step workflow. Because Mastra AI handles retries, this status is crucial for deciding if the process should continue.

Q: Can I create scheduled tasks using Trigger.dev (Background Tasks & Jobs) with Mastra AI?

Yes. You use createschedule to set up time-based jobs that run automatically, fitting right into your workflow's maintenance schedule. The MCP Server ensures these runs are logged and manageable.

Q: Does Trigger.dev (Background Tasks & Jobs) support batch processing for Mastra AI?

It does. You can use createbatch to group tasks that need coordination across different steps. This allows your workflow to treat a set of operations as a single, atomic unit.

Q: How do I cancel a job using Trigger.dev (Background Tasks & Jobs) with Mastra AI?

Calling cancelrun immediately stops an in-progress background task, allowing you to intervene before the workflow reaches a critical point and potentially causes data corruption.

Build Resilient Workflows with Mastra AI (Background Tasks & Jobs) and Automatic Retries.

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Setup Trigger.dev (Background Tasks & Jobs) with Mastra AI

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Perplexity

Orchestrate Complex, Multi-Step Workflows

Mastra AI runs complex workflows that need reliable execution. You can use the MCP Server's tools to manage these steps: triggering a task with `trigger_task`, checking if it succeeded via `get_run`, and then conditionally moving to the next step. This structure lets your agent build powerful business logic. If one part of the process fails, Mastra AI can use its built-in retry mechanism, making sure the overall job completes even when things get messy.

Automated Scheduling and Maintenance

Don't rely on manual triggers for routine maintenance. Use `create_schedule` to define recurring tasks (cron jobs) directly in your Mastra AI workflow. The system handles the timing, and you just monitor it. Need to change a setting? Your agent can update environment variables using `update_env_var`. This means configuration changes are part of the automated, managed process.

Handling Failures Gracefully

The MCP Server provides tools like `replay_run`, which lets your workflow engine re-execute a failed job without manual intervention. You can pinpoint exactly what went wrong by checking the historical data using `list_runs`. If an entire batch fails, you don't restart from scratch. Instead, you use `get_batch_results` to identify the failed components and target them with specific fixes.

Setup guide

Set up Trigger.dev (Background Tasks & Jobs) 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 Trigger.dev (Background Tasks & Jobs) 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: "triggerdev-background-tasks-jobs-mcp-client",
  servers: {
    "triggerdev-background-tasks-jobs-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

const result = await agent.generate(
  "List recent Trigger.dev (Background Tasks & Jobs) transactions"
);
console.log(result.text);

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Common questions about Trigger.dev (Background Tasks & Jobs) MCP in Mastra AI

You use `get_run` to check the live status of a background task within your multi-step workflow. Because Mastra AI handles retries, this status is crucial for deciding if the process should continue.

Yes. You use `create_schedule` to set up time-based jobs that run automatically, fitting right into your workflow's maintenance schedule. The MCP Server ensures these runs are logged and manageable.

It does. You can use `create_batch` to group tasks that need coordination across different steps. This allows your workflow to treat a set of operations as a single, atomic unit.

It touches run metadata, task identifiers, and environment variables. These are the operational parameters that define how your complex workflows execute and fail gracefully.

Calling `cancel_run` immediately stops an in-progress background task, allowing you to intervene before the workflow reaches a critical point and potentially causes data corruption.

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