How to Use the Axle MCP in CrewAI

Q: How do I connect Axle to CrewAI?

Install the crewaitools package. Pass your Vinkius HTTP endpoint directly into the mcps array of your agent definition.

Q: Can multiple CrewAI agents use Axle simultaneously?

Yes. Your research agent can pull data with getload while a different agent updates records using updatedriverstatus. They share the same underlying MCP connection.

Q: How do I restrict Axle tools in CrewAI?

Import MCPServerHTTP and apply a toolfilter. This ensures your monitoring agent cannot accidentally trigger write operations like updateload.

Deploy autonomous dispatch crews in CrewAI to monitor fleet locations and manage driver hours.

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Connect Axle MCP to CrewAI

Create your Vinkius account to connect Axle 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 Axle with CrewAI

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Perplexity

Coordinate dispatch via MCP Server

The `get_vehicle_location` and `get_driver_availability` tools allow a monitor agent to constantly evaluate fleet positioning against legal driving hours. When a truck approaches its limit, the agent signals a coordinator to find a replacement. Handoffs happen automatically. The coordinator uses `list_drivers` to find available personnel nearby, then commands a dispatcher agent to execute `update_load` with the new assignment.

Process shipping paperwork

Extracting bills of lading requires the `list_documents` tool to pull scanned records for completed shipments. An auditor agent reviews these files, verifying the delivery signatures against the original freight orders. Shared memory keeps the crew synchronized. Once the auditor validates the paperwork, it stores the confirmation in memory so the billing agent knows it can finalize the invoice.

Verify logistics connections

Firing `get_account_check` lets a supervisor agent confirm the logistics API is online before launching a massive route optimization task. This prevents the entire crew from failing mid-execution. Restricting access prevents accidents. You configure `MCPServerHTTP` with a `tool_filter` so the monitor agent only sees read tools, while only the dispatcher gets access to `update_driver_status`.

Setup guide

Set up Axle 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 Axle tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Axle 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="Axle Analyst",
        goal="Access and analyze Axle data via MCP.",
        backstory="Expert analyst with direct Axle access.",
        tools=mcp_tools,
    )

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

Install the `crewai[tools]` package. Pass your Vinkius HTTP endpoint directly into the `mcps` array of your agent definition.

Yes. Your research agent can pull data with `get_load` while a different agent updates records using `update_driver_status`. They share the same underlying MCP connection.

Import `MCPServerHTTP` and apply a `tool_filter`. This ensures your monitoring agent cannot accidentally trigger write operations like `update_load`.

CrewAI supports stdio, SSE, and Streamable HTTP. Vinkius provides a streamable HTTP endpoint that handles the logistics queries perfectly.

Driver profiles and GPS coordinates never leak. The MCP server runs in an ephemeral, zero-trust sandbox, meaning your CrewAI agents fetch only what they need before the environment destroys itself.

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