How to Use the Pan Size Converter MCP in Google ADK

Q: Can I filter tools when using Pan Size Converter with Google ADK?

Yes. You can use a toolnames filter to restrict which functions your agent can access, keeping your implementation clean and secure.

Build enterprise baking agents on Google ADK by integrating precise pan volume math into your Google Cloud workflows.

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Connect Pan Size Converter MCP to Google ADK

Create your Vinkius account to connect Pan Size Converter 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 Pan Size Converter with Google ADK

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Volume analysis for Google ADK agents

Your agents call `calculate_volume` to get precise cubic measurements for any baking project. It integrates into your existing Google Cloud infrastructure for reliable results. By using this MCP, your agent avoids the guesswork that leads to wasted ingredients. It keeps your baking data consistent across your entire agentic workflow.

Automated pan swaps

Use `find_equivalent_pan` to help your agent suggest alternatives when specific sizes are missing from your inventory. This tool returns mathematically sound options that maintain your recipe integrity. It works seamlessly with the long-context capabilities of your Gemini models. Your agent can now reason about complex kitchen constraints without manual intervention.

Dimension verification

The `validate_dimensions` tool ensures that every pan input is valid before your agent proceeds. It prevents logical errors in your automated baking pipelines. Your system catches impossible dimensions instantly. This keeps your agent running on clean data throughout its entire operation.

Setup guide

Set up Pan Size Converter 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 Pan Size Converter 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="Pan Size Converter_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Pan Size Converter 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 Pan Size Converter. 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 Pan Size Converter MCP in Google ADK

You use the McpToolset class to link this MCP to your LlmAgent. It allows your agent to call the tools directly through the Google ADK environment.

Yes. You can use a tool_names filter to restrict which functions your agent can access, keeping your implementation clean and secure.

You can feed your pan inventory data from BigQuery into the agent, then use this MCP to perform the necessary math on that data.

It supports both Stdio and HTTP transports. You choose the one that fits your current Google Cloud deployment strategy.

The MCP strictly processes pan dimensions and volume measurements. It does not access your sensitive user data or external files, keeping your baking calculations isolated.

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