How to Use the Trigger.dev MCP in Vercel AI SDK

Q: How do I get the current status of an ongoing job using Trigger.dev and Vercel AI SDK?

You call getrun(runid) to retrieve the latest details for any task run. Because you're using the Vercel AI SDK, this data streams into your UI instantly—you don't wait on a loading spinner.

Q: Can I check all available deployment environments with Trigger.dev and Vercel AI SDK?

Yep. Just use listenvironments. This function shows every defined environment in your project, letting your agent confirm the proper scope before running any code.

Q: What happens if I need to stop a runaway task using Trigger.dev and Vercel AI SDK?

You use cancelrun(runid) to send the cancellation signal. The resulting status is streamed back through your agent, letting you report the failure state right in your application.

Q: How does Trigger.dev handle scheduling visibility with Vercel AI SDK?

You call listschedules to see all configured cron jobs and recurring tasks. This data lets your agent build a view of the system's automated processes for the user.

Get live status updates from Trigger.dev right inside your Vercel AI SDK app.

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Connect Trigger.dev MCP to Vercel AI SDK

Create your Vinkius account to connect Trigger.dev to Vercel AI SDK 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 Trigger.dev with Vercel AI SDK

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Monitor Task Runs in Real Time

You can start and track background jobs using `trigger_task` and immediately see the results by calling `list_runs`. This lets your agent check task status, ensuring the user sees data appear live as the job executes. Furthermore, if a run fails or needs immediate checking, you'll use `get_run(run_id)` to pull specific details. The Vercel AI SDK streams this info directly into the UI, skipping any loading spinners.

Manage Deployment Scope

Before triggering anything, your agent needs context. Call `list_projects` and `list_environments` to see every available scope in Trigger.dev. This prevents running tasks against the wrong deployment target. This helps build user-facing products where the end user sees the AI working live by confirming which environment the task will impact.

Review and Halt Jobs

Sometimes you need to stop a job that's going wrong. You can call `cancel_run(run_id)` to halt an active task immediately. The SDK handles this cancellation result and displays it in the UI. Need to check old work? Use `list_schedules` to see what runs are set up, or even use `replay_run` to re-execute a completed task for verification.

Setup guide

Set up Trigger.dev MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all Trigger.dev tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent Trigger.dev transactions",
});

console.log(text);
await mcpClient.close();

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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 Trigger.dev. 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 Trigger.dev MCP in Vercel AI SDK

You call `get_run(run_id)` to retrieve the latest details for any task run. Because you're using the Vercel AI SDK, this data streams into your UI instantly—you don't wait on a loading spinner.

Yep. Just use `list_environments`. This function shows every defined environment in your project, letting your agent confirm the proper scope before running any code.

You use `cancel_run(run_id)` to send the cancellation signal. The resulting status is streamed back through your agent, letting you report the failure state right in your application.

You call `list_schedules` to see all configured cron jobs and recurring tasks. This data lets your agent build a view of the system's automated processes for the user.

It handles run details, which include task execution logs, run IDs, and job status information. This is all operational metadata from Trigger.dev's background jobs.

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