How to Use the Machinery Cost Calculator MCP in Google ADK

Q: Can I restrict which tools from the Machinery Cost Calculator are exposed to Google ADK?

Yes. You can use the optional toolnames filter when initializing the toolset to expose only the specific calculation tools your agent needs.

Feed agricultural cost metrics directly to Gemini models using Google ADK with native BigQuery and Vertex integration.

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Connect Machinery Cost Calculator MCP to Google ADK

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Setup Machinery Cost Calculator with Google ADK

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Run BigQuery data through Google ADK cost tools

The `calculate_hourly_costs` tool pulls machine telemetry and fuel rates directly from your enterprise data warehouse to compute exact operating expenses. Your agent processes these variables across your entire fleet without manual data entry. This MCP tool brings real-time financial modeling to your cloud database. You get clean, hourly cost metrics calculated directly within your existing data pipeline.

Evaluate regional field expenses at scale

We use the `calculate_area_impact` tool to combine geographic field data with machinery operating costs. Your agent calculates the precise cost per hectare by adjusting for field shape, soil conditions, and equipment efficiency. This tool helps enterprise farms optimize their seasonal budgets. It highlights which fields are costing you the most money per acre.

Analyze fleet ownership versus leasing models

The `compare_ownership_models` tool runs deep financial comparisons between owning heavy machinery and outsourcing to local contractors. Your agent evaluates long-term depreciation, interest rates, and maintenance overhead against flat third-party fees. This lets your procurement agents make data-backed purchasing decisions. It ensures you never overpay for fleet capacity when leasing is the cheaper option.

Setup guide

Set up Machinery Cost Calculator 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 Machinery Cost Calculator 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="Machinery Cost Calculator_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Machinery Cost Calculator 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 Machinery Cost Calculator. 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 Machinery Cost Calculator MCP in Google ADK

You initialize the McpToolset with the streamable HTTP transport parameters and pass it directly to your LlmAgent. The agent instantly recognizes the cost calculation tools.

Yes. You can use the optional tool_names filter when initializing the toolset to expose only the specific calculation tools your agent needs.

Your agent can ingest thousands of pages of fleet telemetry and historical invoices, then use the calculation tools to extract and process exact hourly costs in a single run.

You can run the setup anywhere. The transport layer supports both local stdio and remote HTTP connections, letting you choose the deployment style that fits your architecture.

Yes. All telemetry data and fleet cost variables are processed locally through your transport layer, ensuring your sensitive business metrics never leave your secured Google Cloud perimeter.

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