How to Use the Dashdoc MCP in Google ADK

Q: Can Gemini agents filter Dashdoc transport tools?

You can apply a toolnames filter when setting up the toolset. This restricts the agent to specific operations, like only allowing it to check truck statuses rather than modifying addresses.

Connect Dashdoc to Google ADK to let Gemini agents analyze transport orders, cross-reference BigQuery logistics data, and manage fleets.

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Connect Dashdoc MCP to Google ADK

Create your Vinkius account to connect Dashdoc 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 Dashdoc with Google ADK

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Gemini Agents Query Dashdoc MCP Server

Tools like `search_transports_by_reference` and `get_transport_details` feed raw logistics data straight into Gemini's 1M+ token context window. Your agent can ingest thousands of historical status logs and cargo items in a single pass. Cross-referencing enterprise data happens instantly. An agent can pull a transport order from Dashdoc and immediately compare the scheduling timestamps against supply chain records stored in BigQuery.

Fleet Capacity Planning

The `list_fleet_trucks` and `list_fleet_trailers` tools expose maximum load capacities, trailer types, and current operational status to your Google Cloud environment. Your Gemini agent reads these arrays to determine which vehicles are available for dispatch. Developers building on Vertex AI can use this data to build predictive maintenance agents. The model analyzes tautliner registration numbers and fleet assignment statuses to flag trucks due for inspection.

Contact & Location Mapping

Your agent resolves business partner identities and GPS coordinates using `list_transport_contacts` and `list_saved_addresses`. It pulls tax identifiers, legal names, and specific gate codes into the reasoning loop. Adding new locations happens through `create_new_address`. The agent persists the new site metadata and returns the system ID, keeping your Dashdoc address book synchronized with your internal Google Cloud applications.

Setup guide

Set up Dashdoc 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 Dashdoc 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="Dashdoc_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Dashdoc 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 Dashdoc. 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 Dashdoc MCP in Google ADK

Install google-adk and configure McpToolset using StreamableHttpServerParameters. Pass the resulting toolset directly to your LlmAgent constructor.

You can apply a tool_names filter when setting up the toolset. This restricts the agent to specific operations, like only allowing it to check truck statuses rather than modifying addresses.

The framework natively supports HTTP transports for remote servers. You provide the Vinkius endpoint URL and the agent handles the connection automatically.

Gemini models excel at long-context reasoning. You can dump massive arrays of transport orders into the prompt without hitting token limits.

The ephemeral Vinkius environment isolates your operations entirely. Maximum load capacities, driver names, and customer IDs pass securely between the sandbox and your Google Cloud project without leaving traces.

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