How to Use the Trigger.dev MCP in CrewAI

Q: How do I monitor running processes using Trigger.dev and CrewAI?

A monitoring agent calls listruns to get a comprehensive list of all tasks, letting the crew know what's currently happening. You can then drill down on any specific job with getrun(runid).

Q: Can CrewAI manage scheduled jobs in Trigger.dev?

Yes. Use listschedules to view all configured cron schedules. This lets your autonomous crew agent understand the system's routine maintenance tasks and when they will execute.

Q: What if an agent needs to stop a runaway task with Trigger.dev and CrewAI?

The team uses cancelrun(runid) to halt unexpected processes. This function provides immediate feedback that the job has been successfully terminated for cleanup.

Q: How does Trigger.dev help an autonomous crew with project boundaries?

Agents use listprojects and listenvironments to confirm the available scope. This ensures the entire collaborative team is working within the correct, defined operational area.

Coordinate specialized agents using CrewAI to monitor and manage Trigger.dev workflows autonomously.

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Create your Vinkius account to connect Trigger.dev to CrewAI 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 CrewAI

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Monitor System Status

A monitoring agent uses `list_runs` to gather a full list of all active or recent task runs across the system. This allows the crew to quickly assess operational health. A specialized analysis agent can then use `get_run(run_id)` to pull deep status reports on any single run, which informs subsequent decision-making.

Initiate and Rerun Tasks

If a workflow needs action, one agent triggers it using `trigger_task`. If the initial data was bad, another specialist agent can use `replay_run(run_id)` to re-execute the task with corrected inputs. This capability allows for fully autonomous operations: detect failure, correct input, and restart.

Determine Operational Scope

Before deployment or action, agents must know where they are working. They call `list_projects` and `list_environments` to define the boundaries of their operation. This is critical for multi-agent teams that need shared memory regarding which project scope they're currently in.

Setup guide

Set up Trigger.dev MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Trigger.dev tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Trigger.dev Analyst",
    goal="Access and analyze Trigger.dev data via MCP.",
    backstory="Expert analyst with direct Trigger.dev access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Trigger.dev transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Trigger.dev Analyst",
        goal="Access and analyze Trigger.dev data via MCP.",
        backstory="Expert analyst with direct Trigger.dev access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Trigger.dev transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

Get your connection token →

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 CrewAI

A monitoring agent calls `list_runs` to get a comprehensive list of all tasks, letting the crew know what's currently happening. You can then drill down on any specific job with `get_run(run_id)`.

Yes. Use `list_schedules` to view all configured cron schedules. This lets your autonomous crew agent understand the system's routine maintenance tasks and when they will execute.

The team uses `cancel_run(run_id)` to halt unexpected processes. This function provides immediate feedback that the job has been successfully terminated for cleanup.

Agents use `list_projects` and `list_environments` to confirm the available scope. This ensures the entire collaborative team is working within the correct, defined operational area.

It deals with project definitions, environment scopes, and detailed task run logs, giving your crew access to all necessary metadata for monitoring and escalation.

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