How do I get my Trigger.dev API key?

Log in to your Trigger.dev dashboard at **cloud.trigger.dev**. Open your project, then find the **API Keys** section in the project settings. Copy your **Secret API Key** (it starts with `tr_dev_` for development or `tr_prod_` for production). Paste it into the configuration field below. For Personal Access Tokens (used for admin operations), go to **Profile → Personal Access Tokens** tab instead.

Can my AI agent tell me why a background job failed in production?

Yes. Ask your agent to list failed runs and it returns the task name, error message, stack trace, execution duration, and retry count for each failure. You can then drill into a specific run to see the exact input payload and which step failed — cutting your debugging time from minutes to seconds.

What if I'm on-call and need to check job health at 2 AM?

Just ask your AI agent 'Are there any failed jobs in production?' and get an instant triage report — number of failures, which tasks are affected, when they started failing, and whether retries resolved them. No need to open a browser, log in, or navigate dashboards in the middle of the night.

Does it support multiple environments like dev, staging, and production?

Yes. Each API key is scoped to a specific environment (dev or prod), just like in Trigger.dev itself. You can configure separate integrations for each environment, or switch between them by updating the API key — giving you full control over which environment your AI agent queries.

Trigger.dev MCP Server for CrewAI 8 tools — connect in under 2 minutes

Name: Trigger.dev
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

Connect your CrewAI agents to Trigger.dev through Vinkius, pass the Edge URL in the `mcps` parameter and every Trigger.dev tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Trigger.dev Specialist",
    goal="Help users interact with Trigger.dev effectively",
    backstory=(
        "You are an expert at leveraging Trigger.dev tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Trigger.dev "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 8 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Trigger.dev MCP Server

Connect Trigger.dev to your AI agent and manage your background job infrastructure conversationally.

When paired with CrewAI, Trigger.dev becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Trigger.dev tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Job Monitoring — List active, completed, and failed task runs with execution times, statuses, and error details.
Project Overview — Query projects, environments, and their associated job definitions.
Run Inspection — Drill into individual runs to view payloads, outputs, logs, and retry history.
Environment Management — Switch between dev, staging, and production environments to inspect runs across your deployment pipeline.

The Trigger.dev MCP Server exposes 8 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Trigger.dev to CrewAI via MCP

Follow these steps to integrate the Trigger.dev MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 8 tools from Trigger.dev

Why Use CrewAI with the Trigger.dev MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Trigger.dev through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Trigger.dev + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Trigger.dev MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Trigger.dev for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Trigger.dev, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Trigger.dev tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Trigger.dev against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Trigger.dev MCP Tools for CrewAI (8)

These 8 tools become available when you connect Trigger.dev to CrewAI via MCP:

cancel_run

Cancel a running task

get_run

Get run details

list_environments

List deployment environments

list_projects

List all projects

list_runs

List task runs

list_schedules

List cron schedules

replay_run

Replay a completed task

trigger_task

Trigger a background task

Example Prompts for Trigger.dev in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Trigger.dev immediately.

"Are there any failed background jobs in production?"

"Show me the details of the last 'process-webhook' run."

"How many jobs ran successfully today?"

Troubleshooting Trigger.dev MCP Server with CrewAI

Common issues when connecting Trigger.dev to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Trigger.dev + CrewAI FAQ

Common questions about integrating Trigger.dev MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.