How to Use the Pando MCP in Google ADK

Q: Can I query Pando carrier lists using Google ADK with BigQuery data?

Yes, your agent can pull active carrier data with listcarriers and join it with historical performance metrics stored in BigQuery. This helps the model select carriers based on actual delivery performance.

Connect your logistics data directly to Gemini models using the Google ADK to automate freight routing.

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Connect Pando MCP to Google ADK

Create your Vinkius account to connect Pando to Google ADK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Pando with Google ADK

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Run high-volume route queries with Google ADK

The `list_routes` tool lets your Gemini agent analyze configured shipping lanes directly within the Google Cloud ecosystem. This integration allows your model to process massive token windows of route history to identify bottlenecks. By combining these routes with BigQuery data, your enterprise agent makes smart logistics decisions. Vinkius ensures your cloud-hosted models query live transport paths without manual exports.

Automate vehicle matching and carrier dispatch

The `list_vehicles` tool provides your Google ADK agent with a real-time list of registered trucks and trailers. Your agent compares this list against active shipment demands to find the right vehicle size. Once matched, the agent uses `create_indent` to book the vehicle instantly. This automated loop reduces the time dispatchers spend on the phone securing capacity.

Track warehouse capacity and material locations

The `list_locations` tool maps your warehouse network directly into the Gemini context window. Your agent references these physical locations to coordinate incoming freight and avoid dock congestion. It cross-references this spatial data with `list_materials` to verify which sites can receive specific cargo types. This prevents expensive routing errors before trucks leave the yard.

Setup guide

Set up Pando 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 Pando 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="Pando_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Pando tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Pando MCP in Google ADK

You instantiate the tools using the McpToolset class in Python. This exposes Pando's logistics endpoints directly to your Gemini agent, enabling automated route queries.

Yes, your agent can pull active carrier data with `list_carriers` and join it with historical performance metrics stored in BigQuery. This helps the model select carriers based on actual delivery performance.

Vinkius handles the underlying MCP authentication natively so your enterprise agents only need a single endpoint token. This keeps your logistics credentials safe within your Google Cloud environment.

You should use the HTTP transport option in the toolset to prevent timeouts. This allows your agent to fetch massive shipment logs using `list_shipments` using the MCP Server HTTP transport.

Your physical warehouse maps and inventory lists remain encrypted end-to-end. Vinkius runs the adapter in ephemeral, isolated sandboxes, meaning your proprietary supply chain layout is never cached or stored using this MCP integration.

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