How to Use the Giddyup MCP in Google ADK

Q: How do I restrict which Giddyup tools are exposed to my Google ADK agent?

Use the toolnames filter when initializing your McpToolset in Python. This lets you restrict access to sensitive operations like listinvoices while keeping listjobs open.

Q: How do I connect Google ADK to the Giddyup server over HTTP?

Initialize the McpToolset with the secure HTTP URL provided by your Vinkius dashboard. This establishes a secure connection to the managed MCP Server without requiring local configuration.

Q: How does Google ADK protect Giddyup customer and lead data?

All lead information retrieved via getlead or modified via updatelead is processed in transit. Vinkius uses ephemeral sandboxes to ensure your field service contact details are never logged or stored.

Connect your Giddyup construction dispatch tools to Gemini models and BigQuery using the Google ADK.

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Connect Giddyup MCP to Google ADK

Create your Vinkius account to connect Giddyup 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 Giddyup with Google ADK

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Long-context job analysis with Google ADK

The `list_jobs` tool pulls your entire Giddyup construction schedule directly into the Google ADK long-context window. Because Gemini models handle million-token inputs, your agent can analyze months of dispatch history alongside real-time updates from `get_job`. It turns messy schedules into clear operational insights. This allows Gemini models to analyze Giddyup technician availability alongside Vertex AI routing data. You can feed the output of `list_users` directly into your cloud models to optimize dispatch routes. It is built for heavy, enterprise-scale logistics.

Connect BigQuery data to Giddyup workflows

The `create_lead` tool lets your Google ADK agent turn BigQuery database insights into active Giddyup field opportunities. Your agent can query historical customer data in Google Cloud, identify high-value construction accounts, and immediately write them to your pipeline. It bridges the gap between cloud analytics and physical jobs. The agent coordinates the transition, using `get_customer` to verify Google Cloud customer profiles before updating Giddyup. You don't have to manually export CSVs or run sync scripts anymore. It just works.

Enterprise dispatching via Google Cloud ADK

The `update_job` tool updates Giddyup field dispatch statuses directly from your Google ADK pipeline. By linking this MCP Server to your Google Cloud setup, your models can modify schedules based on real-time weather alerts or traffic delays. It keeps your field crews moving efficiently. The integration runs inside a zero-trust V8 sandbox managed by Vinkius, protecting your Giddyup `update_lead` workflows. Gemini models safely execute these actions without exposing your internal infrastructure. You get secure, automated dispatching at scale.

Setup guide

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

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Common questions about Giddyup MCP in Google ADK

Use the `tool_names` filter when initializing your `McpToolset` in Python. This lets you restrict access to sensitive operations like `list_invoices` while keeping `list_jobs` open.

Yes, Gemini's large context window easily manages all 13 tools, including `list_users` and `update_lead`. The model selects the correct tool based on your natural language dispatch requests.

Initialize the `McpToolset` with the secure HTTP URL provided by your Vinkius dashboard. This establishes a secure connection to the managed MCP Server without requiring local configuration.

No, Vinkius manages the Giddyup credentials for you. Your agent uses a single MCP endpoint token to execute tools securely.

All lead information retrieved via `get_lead` or modified via `update_lead` is processed in transit. Vinkius uses ephemeral sandboxes to ensure your field service contact details are never logged or stored.

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