How to Use the Chi-Square Test Engine MCP in Google ADK

Run exact categorical tests directly from your BigQuery data using Google ADK and this dedicated MCP Server.

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Connect Chi-Square Test Engine MCP to Google ADK

Create your Vinkius account to connect Chi-Square Test Engine 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 Chi-Square Test Engine with Google ADK

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Direct BigQuery data testing via Google ADK

The `calculate_chi_square` tool integrates with your Google ADK agent to evaluate categorical datasets pulled straight from BigQuery. Instead of dumping raw tables into Gemini's context window and hoping the model gets the math right, the agent routes the data directly to our CPU-backed statistical engine. This keeps your token usage low and your results perfectly accurate. Your enterprise agent can pull millions of rows, aggregate them into a contingency table, and get instant p-values without leaving your Google Cloud pipeline.

Long-context reasoning meets exact math

The `calculate_chi_square` tool allows Gemini models to analyze massive datasets without losing statistical accuracy. While the model handles high-level reasoning across thousands of pages of documentation, it delegates the actual math to this specialized tool. This separation of labor means Gemini does what it does best—reasoning—while our engine handles the heavy lifting of calculating degrees of freedom and chi-square statistics.

Secure enterprise deployment for your MCP Server

The `calculate_chi_square` tool deploys via the Google ADK toolset manager using standard HTTP transports to the MCP Server. You can restrict which Gemini agents have access to this statistical tool using the native tool name filter. This gives your cloud platform team complete control over which agents can run statistical tests, preventing unauthorized access to sensitive backend data.

Setup guide

Set up Chi-Square Test Engine 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 Chi-Square Test Engine 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="Chi-Square Test Engine_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Chi-Square Test Engine tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Chi-Square Test Engine MCP in Google ADK

You instantiate an McpToolset pointing to the Vinkius HTTP endpoint and pass it to your LlmAgent tools list. This exposes the MCP Server directly to Gemini.

Yes, your agent can query BigQuery, format the results into a contingency table, and pass them to the tool. The engine returns the exact test statistics instantly.

Yes, it works with any Gemini model supported by the ADK. The long-context window allows the agent to hold massive tables before passing them to the tool.

The system supports both Stdio and secure HTTP transports. For cloud deployments, the HTTP transport is recommended to connect your hosted agents securely.

Your categorical data is processed entirely in memory inside a secure Google Cloud-adjacent sandbox. No input data is written to persistent storage, ensuring your proprietary business metrics remain completely confidential.

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