How to Use the Upper Route Planner MCP in Google ADK

Q: How do I check the status of Upper Route Planner using Google ADK?

Use checkupperstatus. The tool confirms system availability. Because you're building enterprise agents, this initial validation step is critical before running large batch jobs.

Q: Can I list active routes using Upper Route Planner with Google ADK?

Yes. The agent calls listupperroutes to pull all current paths. These route manifests can then be passed to Gemini for advanced optimization and analysis.

Q: Does this MCP Server support multi-driver operations with Google ADK?

It does. First, you list the drivers using listupperdrivers, then pass that comprehensive dataset into the createupperdeliverytask tool to schedule coordinated movements.

Q: How do I retrieve details for an upper route stop using Upper Route Planner and Google ADK?

Run getupperroutestop with the necessary identifiers. This gives you precise data points that can be used by your agent to reason about optimal path adjustments within Vertex AI.

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Connect Upper Route Planner MCP to Google ADK

Create your Vinkius account to connect Upper Route Planner 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 Upper Route Planner with Google ADK

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Creating Deliveries for the MCP Server

You use `create_upper_delivery_task` to schedule a new delivery run. Since you're working in the Gemini ecosystem, your agent can process complex inputs and map them directly into structured data fields. This tool allows you to add tasks while ensuring the necessary geographic and temporal constraints are met for successful deployment.

Querying Driver Information

`list_upper_drivers` pulls a list of all available drivers. The agent can take this structured data and cross-reference it with other enterprise sources, like BigQuery, to check operational availability. When you need to know who's out there, the tool gives you reliable driver identifiers that your Google Cloud workflow can act upon.

Getting Stop Details from Upper Route Planner

To get full details on a single location, invoke `get_upper_stop_details`. The agent holds long-context reasoning and can use the returned stop data to make complex decisions about routing changes. This function provides all necessary information—from coordinates to operational hours—so your enterprise models don't have to guess anything.

Setup guide

Set up Upper Route Planner 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 Upper Route Planner 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="Upper Route Planner_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Upper Route Planner 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 Upper Route Planner. 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 Upper Route Planner MCP in Google ADK

Use `check_upper_status`. The tool confirms system availability. Because you're building enterprise agents, this initial validation step is critical before running large batch jobs.

The server handles delivery tasks, route stops, and driver profiles. Since you're integrating with BigQuery, this structured output fits cleanly into your existing enterprise datasets.

Yes. The agent calls `list_upper_routes` to pull all current paths. These route manifests can then be passed to Gemini for advanced optimization and analysis.

It does. First, you list the drivers using `list_upper_drivers`, then pass that comprehensive dataset into the `create_upper_delivery_task` tool to schedule coordinated movements.

Run `get_upper_route_stop` with the necessary identifiers. This gives you precise data points that can be used by your agent to reason about optimal path adjustments within Vertex AI.

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