How to Use the Missing Value Imputer MCP in Google ADK

Q: How do I connect Missing Value Imputer to Google ADK?

Use McpToolset with the server HTTP parameters pointing to your Vinkius endpoint. Pass this toolset into your LlmAgent constructor to expose the imputation tools to Gemini.

Feed clean, NaN-free data directly to your Gemini models using Google ADK and local deterministic imputation.

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Connect Missing Value Imputer MCP to Google ADK

Create your Vinkius account to connect Missing Value Imputer 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 Missing Value Imputer with Google ADK

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Run impute_missing_values on BigQuery data

The `impute_missing_values` tool processes tables pulled from your cloud storage or databases. Your Google ADK agent pulls raw data, runs the local imputation, and feeds clean tables straight to Gemini. This approach avoids sending uncleaned data into your long-context windows. You save token budget by stripping out NaN noise before your agent analyzes the dataset.

Local data preparation for Google ADK agents

The `impute_missing_values` tool executes calculations locally using your chosen mathematical strategy. Google ADK routes the tool call through a secure transport layer, ensuring the agent gets immediate, predictable results. This MCP Server doesn't rely on model heuristics to guess missing values. It uses strict mean, median, mode, or zero strategies to keep your data pipelines mathematically sound.

Restrict tools inside your Gemini enterprise loop

The `impute_missing_values` tool can be isolated using the `tool_names` filter in your agent setup. This ensures your Google ADK agent only accesses data cleaning functions over the MCP connection. Limiting the agent's scope prevents unintended actions during complex data analysis jobs. Your pipeline stays focused on cleaning data without exposing extra system access.

Setup guide

Set up Missing Value Imputer 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 Missing Value Imputer 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="Missing Value Imputer_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Missing Value Imputer tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Missing Value Imputer MCP in Google ADK

Use `McpToolset` with the server HTTP parameters pointing to your Vinkius endpoint. Pass this toolset into your `LlmAgent` constructor to expose the imputation tools to Gemini.

Yes, your agent can read data from BigQuery, pass the raw records to the tool, and write the clean, imputed dataset back to Google Cloud. The tool handles the NaN values locally before write-back.

The agent can choose Mean, Median, Mode, or Zero. It specifies the strategy in the tool call, and the server executes the math deterministically on the target columns.

Yes, Google ADK supports both Stdio and HTTP transports. For hosted Vinkius environments, HTTP streamable transport is the standard way to connect your agents.

Your datasets stay safe because all NaN calculations occur within an ephemeral, zero-trust V8 sandbox. No data is stored, and the raw tables never touch external AI training loops during the imputation process.

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