How to Use the Hydration Calculator MCP in Google ADK

Use the Hydration Calculator with Google ADK to integrate baking science into BigQuery.

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Connect Hydration Calculator MCP to Google ADK

Create your Vinkius account to connect Hydration 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 Hydration Calculator with Google ADK

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Baking Logic for Your Agent

Need to predict dough texture? The MCP Server helps your agent classify the structure by using a mix of hydration percentage and profile name. This logic fits right into your enterprise workflow. Because you're building agents on Google Cloud, this tool lets you perform complex baking calculations directly against data already stored in BigQuery.

MCP Server Integration for Data Scientists

The MCP Server calculates dough hydration percentage by taking flour and liquid weights. This is perfect for feeding raw manufacturing inputs into your long-context reasoning models. You can pass this calculated data through the agent to determine what kind of baked good, like bread or focaccia, you're actually dealing with.

Running Complex Baking Models

This tool set also lets your agent identify the dough type using flour and salt composition. It’s a multi-step process that runs entirely through the MCP Server. Your long context reasoning with Gemini models can then use this specific, validated output to make high-level strategic decisions.

Setup guide

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

You pass ingredient weights and profile data through the MCP toolset. The agent executes the calculation, bringing precise hydration percentages right back to your BigQuery environment for analysis.

Yes. You can input various flour and liquid weights; the MCP Server will calculate the percentage, which you'll then use to classify the texture or determine the appropriate dough type.

It handles quantitative ingredient measurements (weights) and qualitative profile names. This makes it useful for classifying textures and identifying suitable baked goods.

Yes. The MCP Server is designed to act as a validated, external service that your agent calls only when necessary, keeping your core models clean and focused on high-level reasoning.

The server touches ingredient weights (flour/liquid) and baking profiles. This is all necessary for determining both the calculated percentage and the resulting dough type.

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