How to Use the HyperTrack MCP in Google ADK

Q: How do I register the HyperTrack tools inside a Google ADK project?

Install the package using pip install google-adk. Initialize your connection with McpToolset pointing to the Vinkius HTTP endpoint, then pass that toolset object directly into the tools list of your LlmAgent.

Q: Can I combine HyperTrack telemetry with BigQuery data inside Google ADK?

Yes. Your agent can query live tracking data via getdevice and cross-reference it with historical performance tables in BigQuery. This allows Gemini to analyze real-time delays against seasonal traffic trends.

Q: Can I filter which tools this MCP Server exposes to my Gemini agent?

Yes, you can use the optional toolnames filter in the McpToolset configuration. This lets you limit the agent's access to read-only tools like getgeofence while blocking write operations.

Feed live telemetry and dispatch data directly to Gemini models using the Google ADK framework.

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Connect HyperTrack MCP to Google ADK

Create your Vinkius account to connect HyperTrack to Google ADK 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 Google ADK

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Enterprise fleet coordination using Gemini and Google ADK

The `list_devices` and `get_device` tools feed real-time hardware status and live coordinates directly into your Gemini agent's context window. This allows your agent to match physical fleet positions against warehouse locations stored in BigQuery. This MCP Server routes raw coordinates directly to Gemini. You can pass these live coordinates to Vertex AI models to optimize multi-stop delivery routes.

Managing active shipments via this MCP Server

The `get_order` and `list_orders` tools retrieve active delivery statuses, destination addresses, and customer fulfillment requirements. Your agent queries these endpoints to identify stalled orders and assign them to nearby active drivers. Because Google ADK handles long-context inputs, your agent can analyze hundreds of order profiles from `list_orders` simultaneously. This makes it easy to spot systemic transit bottlenecks across your entire distribution network.

Automated field worker dispatching and tracking

The `get_worker` and `list_workers` tools expose worker profiles, active statuses, and current assignments. Your agent uses this information to coordinate field operations, matching urgent tickets with the closest available technician. By combining worker data with geofence logs from `list_geofences`, the agent tracks job completion times. You get automated performance reporting without asking workers to manually log hours.

Setup guide

Set up HyperTrack MCP in Google ADK

Prerequisites

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

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with HyperTrack tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="HyperTrack_agent",
    model="gemini-2.0-flash",
    instruction="You have access to HyperTrack tools via MCP.",
    tools=mcp_tools,
)

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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 Google ADK

Install the package using `pip install google-adk`. Initialize your connection with `McpToolset` pointing to the Vinkius HTTP endpoint, then pass that toolset object directly into the `tools` list of your `LlmAgent`.

Yes. Your agent can query live tracking data via `get_device` and cross-reference it with historical performance tables in BigQuery. This allows Gemini to analyze real-time delays against seasonal traffic trends.

The framework relies on your agent's execution loop to control polling frequency. You should configure your agent to call `get_trip` or `list_trips` only when specific triggers occur, preventing unnecessary API usage.

Yes, you can use the optional `tool_names` filter in the `McpToolset` configuration. This lets you limit the agent's access to read-only tools like `get_geofence` while blocking write operations.

Your device IDs, coordinates, and worker profiles travel directly between the HyperTrack API and your Google Cloud environment. Vinkius operates as a zero-trust MCP gateway, meaning your telemetry is never logged, cached, or stored on our platform.

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