How to Use the Fuel Cost Calculator MCP in Google ADK

Q: Can I filter tools in Fuel Cost Calculator for Google ADK?

Yes, you can use the toolnames filter to restrict which MCP tools your agent can access. This gives you fine-grained control over the agent's capabilities.

Deploy enterprise agents on Google Cloud with Fuel Cost Calculator. Connect your Gemini agents to live fuel market data.

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Connect Fuel Cost Calculator MCP to Google ADK

Create your Vinkius account to connect Fuel Cost Calculator 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 Fuel Cost Calculator with Google ADK

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Get accurate trip costs on Google Cloud

Use `calculate_trip_cost` to feed fuel expenditure data into your BigQuery workflows. It lets your Gemini agents process large-scale travel data with ease. This setup works perfectly for enterprise-grade agent pipelines. You get high-fidelity cost data directly from your infrastructure.

Run fuel comparisons for enterprise agents

Your agents can leverage `compare_fuel_efficiency` to make data-driven decisions on fuel economy. It connects your agent's reasoning to real-world market fluctuations. This keeps your agent's advice grounded in current prices. It is a reliable way to manage costs across your fleet operations.

Summarize complex trips for users

Trigger `get_trip_summary` to compile all cost factors into a structured report for your Gemini agents. It handles the heavy lifting of summarization for you. Your agents can then present this to the user in a clear, formatted response. It works seamlessly with your existing cloud-native tools.

Setup guide

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

Use the McpToolset class with your server parameters and pass it to the LlmAgent constructor. It is designed for quick integration into your cloud agent setup.

Yes, you can use the tool_names filter to restrict which MCP tools your agent can access. This gives you fine-grained control over the agent's capabilities.

The output of these tools can be piped directly into your BigQuery datasets for further analysis. It bridges the gap between agent logic and your data warehouse.

It supports secure HTTP transports to ensure your agent's communication is encrypted. Your data remains protected throughout the transit between your cloud agent and the MCP.

It touches data related to fuel price, vehicle efficiency, and total distance. This information is processed in an isolated manner, ensuring your sensitive fleet data remains private.

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