Trigger.dev connector for AI agents

Tools your jobs agent reaches for on Trigger.dev, scoped per user.

CALL ANY TOOL

59 tools for background jobs on Trigger.dev: trigger, batch, replay, and cancel runs, read run traces and results, manage schedules, queues, concurrency limits, and environment variables, triage errors, and query run data with TRQL.

triggerdev_abort_bulk_action

Abort bulk action

Abort a pending bulk action so it stops processing more runs. Runs already processed are not undone. Returns the updated bulk action. Use get_bulk_action to see how far it got.

Parameters

Name

Type

Required

Description

bulk_action_id

string

Required

ID of the bulk action, starting with bulk_.

triggerdev_add_run_tags

Add run tags

triggerdev_batch_trigger_task

Batch trigger task

triggerdev_batch_trigger_tasks

Batch trigger tasks

triggerdev_cancel_run

Run cancel

triggerdev_complete_waitpoint_token

Complete waitpoint token

triggerdev_create_bulk_action

Create bulk action

triggerdev_create_schedule

Create schedule

triggerdev_delete_env_var

Delete env var

triggerdev_execute_query

Query execute

triggerdev_get_batch

Batch get

triggerdev_get_bulk_action

Get bulk action

triggerdev_get_env_var

Get env var

triggerdev_get_query_schema

Get query schema

triggerdev_get_run

Run get

triggerdev_get_run_trace

Get run trace

triggerdev_ignore_error

Ignore error

triggerdev_list_bulk_actions

List bulk actions

triggerdev_list_concurrency_limits

List concurrency limits

triggerdev_list_env_vars

List env vars

triggerdev_list_query_dashboards

List query dashboards

triggerdev_list_runs

List runs

triggerdev_list_timezones

List timezones

triggerdev_override_concurrency_limit

Override concurrency limit

triggerdev_pause_concurrency_limit

Pause concurrency limit

triggerdev_promote_deployment

Promote deployment

triggerdev_replay_run

Run replay

triggerdev_reset_queue_concurrency

Reset queue concurrency

triggerdev_update_env_var

Update env var

triggerdev_update_run_metadata

Update run metadata

For more tools, view docs.

Build your Agent

Same auth pattern across LangChain, OpenAI, Anthropic, and Google ADK.

import { ScalekitClient } from "@scalekit-sdk/node";
import { createReactAgent } from "@langchain/langgraph/prebuilt";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);

// Trigger.dev tools scoped to this user
const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["triggerdev"], toolNames: [
    "triggerdev_list_runs",
    "triggerdev_get_run_trace",
    "triggerdev_replay_run"] },
  pageSize: 100,
});

const agent = createReactAgent({ llm, tools });
await agent.invoke({ messages: [{ role: "user", content: "Find the sync-invoices runs that failed in the last hour" }] });

import OpenAI from "openai";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);
const openai = new OpenAI();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["triggerdev"] }, pageSize: 100,
});

const res = await openai.chat.completions.create({
  model: "gpt-5",
  messages: [{ role: "user", content: "Find the sync-invoices runs that failed in the last hour" }],
  tools,
});

// Execute the tool call with the user's vaulted Trigger.dev access token
await sk.tools.executeTool(res.choices[0].message.tool_calls[0], "user_123");

import Anthropic from "@anthropic-ai/sdk";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);
const anthropic = new Anthropic();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["triggerdev"] }, pageSize: 100,
});

const msg = await anthropic.messages.create({
  model: "claude-sonnet-5",
  max_tokens: 1024,
  messages: [{ role: "user", content: "Find the sync-invoices runs that failed in the last hour" }],
  tools,
});

// Tool call runs with the user's vaulted Trigger.dev access token
await sk.tools.executeTool(msg.content, "user_123");

import { Agent } from "@google/adk/agents";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["triggerdev"] }, pageSize: 100,
});

const agent = new Agent({
  name: "jobs_agent",
  model: "gemini-2.5-pro",
  instruction: "Trigger.dev tools scoped to this user",
  tools,
});

await agent.run("Find the sync-invoices runs that failed in the last hour");

Try these prompts

Copy any prompt into your agent. Each maps directly to a Trigger.dev tool. Click to copy, paste into your agent, done.

Runs

Copy the prompt

Copied

Trigger the send-digest task with this JSON payload.

Copy the prompt

Copied

Replay run run_8fa2 with the same payload.

Copy the prompt

Copied

Cancel every queued run of the resize-image task.

Debugging

Copy the prompt

Copied

Show the trace for run run_8fa2.

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Copied

List unresolved error groups in production.

Copy the prompt

Copied

What was the success rate of sync-invoices over the last 7 days?

Schedules and deploys

Copy the prompt

Copied

Create a schedule that runs nightly-report at 2am UTC every day.

Copy the prompt

Copied

Pause the email-send queue.

Copy the prompt

Copied

Promote deployment version 20261020.3 to current.

SEE HOW AUTH WORKS

Each user connects their own Trigger.dev access token once, and Scalekit sends it with every call. Tokens stay vaulted, every call is scope checked, and every action is logged.

Authorize

Your user connects

Trigger.dev

once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access

Who:

user ‘A’

when:

Once per user

access:

Limited to user

Store

Their

Trigger.dev

token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection

vault:

encrypted

scope:

per-user

tokens:

auto-refreshed

Resolve

When your agent calls a

Trigger.dev

tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs

speed:

~40ms

check:

before every call

seen by:

nobody

Audit

Every

Trigger.dev

tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it

history:

90 days

export:

SIEM-ready

logged:

every call

Test other agents

See the same per-user auth pattern across other developer tools and automation connectors.

Engineering Teams

DevOps assistant agent

Polls GitHub for failing checks and stale PRs, opens Linear issues for the ones that need work, and posts a daily digest to Slack. It acts as the engineer, not a shared service account.

Engineering Teams

Engineering standup agent

Pulls commits from GitHub and GitLab, tracks issue movement in Jira, and posts a per-engineer standup brief to Slack. Each engineer's activity is read on their own delegated OAuth.

Why Scalekit

Secure your agent's access. Connectors ship in minutes

01.

Shared tokens break per-user analytics

A shared Trigger.dev access token looks fine in a demo. In production every triggered run looks like one service account, and you cannot tell which user triggered it. Scalekit resolves the credential of the actual user who triggered the agent, never a shared bot.

// shared token
audit → bot_service_account

// scalekit
audit → user_abc ✓

02.

Authentication is not authorization

03.

Multi-tenancy is architectural

04.

Trigger.dev today. Ten connectors tomorrow.

“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”

Venu Madhav Kattagoni

Head of Engineering / Von

FAQs

Frequently Asked Questions

Does the agent access Trigger.dev as the user or through a shared access token?

As the user. Each user connects their own Trigger.dev access token once, and Scalekit sends it with every call. Runs the agent triggers, replays, or cancels are attributed to that user in your audit trail, not a shared service account.

Where is the Trigger.dev access token stored?

In Scalekit's managed AES-256 token vault, namespaced per tenant. To rotate it, the user reconnects with a new access token. Revocation is a single dashboard action. Credentials never appear in prompts, logs, or LLM context.

Can I limit what the agent does in Trigger.dev?

Yes. Filter by tool name in listScopedTools to expose only what you want, for example run and trace read tools without triggerdev_delete_env_var and triggerdev_delete_schedule, which permanently remove a variable or schedule. Scalekit also enforces scope checks before every API call.

What happens when a user revokes Trigger.dev access?

The connection is invalidated on the next tool call. Subsequent requests for that user fail closed with a clear error. Other users in the tenant remain unaffected. The event is logged for audit.

Which Trigger.dev environment does the agent act on?

The environment the connected access token belongs to. Run, queue, schedule, and deployment tools act inside that environment. Environment variable tools take a project_ref to target a specific project environment.