How to Use the Aero Workflow MCP in CrewAI

Q: How can I set up a CrewAI team to manage tasks in Aero Workflow?

Assign one agent the listworkflowtasks tool to monitor for open items. Give a second agent the gettaskdetails and createnewworkflowtask tools to analyze and delegate sub-tasks. CrewAI manages the collaboration between them.

Q: Can I limit which Aero Workflow tools a specific CrewAI agent can use?

Yes. When you initialize the MCPServerHTTP class in CrewAI, you can use the toolfilter argument. This lets you provide a specific list of tool names that a particular agent is allowed to access from this MCP server.

Deploy a crew of autonomous agents to manage your Aero Workflow practice. Let your AI team handle the admin.

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Connect Aero Workflow MCP to CrewAI

Create your Vinkius account to connect Aero Workflow 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 Aero Workflow with CrewAI

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Autonomous Client Management

Give your CrewAI agents the tools to manage your firm's client list. One agent can be tasked with monitoring for new entries, using `list_firm_customers` to get an updated list. Another agent can then take that data and create kickoff tasks with `create_new_workflow_task`. This is how you build a hands-off client onboarding system. The 'Researcher' agent finds the work to be done, and the 'Executor' agent does it, all within Aero Workflow. You just define the roles and goals for your crew.

Let Your AI Crew Balance Workloads

This MCP server gives your agents visibility into your team's work. A 'Manager' agent can use `list_firm_team_members` to see who's on the team and `list_workflow_tasks` to see who's busy. Based on that data, the crew can intelligently assign new work. Instead of just randomly assigning tasks, your agents can make informed decisions, ensuring no single team member gets overloaded. It’s automated resource management.

Automated Auditing with CrewAI

Assign a crew to perform routine checks on your Aero Workflow account. One agent's job could be to periodically run `list_time_tracking_logs` to look for unbilled time. Another could use `list_workflow_emails` to check for communication gaps. This turns tedious manual auditing into a background process. Your CrewAI system can run these checks 24/7 and flag anomalies for a human to review, all by using the tools on this MCP server.

Setup guide

Set up Aero Workflow 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 Aero Workflow tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Aero Workflow transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

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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="Aero Workflow Analyst",
        goal="Access and analyze Aero Workflow data via MCP.",
        backstory="Expert analyst with direct Aero Workflow access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Aero Workflow 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 Aero Workflow. 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 Aero Workflow MCP in CrewAI

Assign one agent the `list_workflow_tasks` tool to monitor for open items. Give a second agent the `get_task_details` and `create_new_workflow_task` tools to analyze and delegate sub-tasks. CrewAI manages the collaboration between them.

Yes. When you initialize the `MCPServerHTTP` class in CrewAI, you can use the `tool_filter` argument. This lets you provide a specific list of tool names that a particular agent is allowed to access from this MCP server.

They don't need to. You provide the Vinkius MCP URL directly in your Agent definition. Vinkius handles the secure, token-based authentication to the Aero Workflow API on behalf of your agents.

Yes, that's a perfect use case. An 'executing' agent can use `create_new_workflow_task`. Then, a 'reviewing' agent can use `list_workflow_tasks` and `get_task_details` to check the work that was done and approve it or flag it for changes.

Yes, access is strictly controlled. The tools on this MCP server only touch the Aero Workflow data necessary for their function, like team member lists or task metadata. Vinkius isolates every tool execution, and your `mcps` URL token ensures only your authorized CrewAI agents can make requests.

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