How to Use the HyperTrack MCP in CrewAI

Coordinate autonomous logistics crews using the HyperTrack MCP Server in CrewAI.

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Connect HyperTrack MCP to CrewAI

Create your Vinkius account to connect HyperTrack 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 HyperTrack with CrewAI

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Perplexity

Multi-agent trip coordination

Assign a research agent to use `list_trips` while an action agent manages the logistics. CrewAI manages the shared memory between these specialized roles. You gain a unified view of your operations. One agent monitors while the other handles the dispatching automatically.

Autonomous geofence monitoring

Deploy a monitor agent to poll `list_geofences` and report violations. CrewAI handles the sequential execution and reporting to your dashboard. This removes the need for manual monitoring. The crew flags issues as they happen, leaving you to manage the exceptions.

Device fleet auditing

Use `list_devices` to have your crew identify hardware issues across the fleet. Agents compare device status against your inventory records. You maintain total visibility. The crew reports back only when a device requires maintenance or shows an error state.

Setup guide

Set up HyperTrack 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 HyperTrack tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Pass the server URL into the agent's MCP configuration list. The agents will then gain access to all available tools for their assigned tasks.

You can use the tool filter feature to restrict access. This ensures that agents only interact with the specific endpoints you authorize.

The framework uses shared memory to pass results between agents. One agent fetches the trip details, and the next agent uses that data to perform an action.

It supports standard HTTP and SSE transports. You pick the one that fits your deployment environment for the most reliable performance.

Access is restricted to the specific API calls defined in your tools. No raw data is cached on the server, and every request requires a valid endpoint token.

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