How to Use the Amazon Redshift MCP in Google ADK

Q: What happens if an Amazon Redshift query fails in Google ADK?

The statementstatus tool provides the error details returned by the Redshift Data API. Your agent can catch these errors and potentially retry or report the failure.

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Connect Amazon Redshift MCP to Google ADK

Create your Vinkius account to connect Amazon Redshift 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 Amazon Redshift with Google ADK

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Map Amazon Redshift tables with Google ADK

Your agent maps out the warehouse by calling `list_schemas` to find the right data set. It then uses `list_tables` to pinpoint specific targets. This provides your agent with a full map of your data. It stops the model from hallucinating table names that don't exist in your cluster.

Execute complex SQL via Google ADK

The agent sends commands through `execute_sql` to process large data sets. It acts as a bridge between your Gemini-powered logic and your actual warehouse storage. This setup allows for deep reasoning over your data. Your agent can digest large query results and explain them based on your business logic.

Monitor status in Google ADK

Check the progress of your queries by calling `statement_status` frequently. This ensures your agent knows exactly when it can move to the next step of the pipeline. It removes the guesswork from agent workflows. You get reliable feedback on whether your data operation succeeded or failed.

Setup guide

Set up Amazon Redshift 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 Amazon Redshift 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="Amazon Redshift_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Amazon Redshift 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 Amazon Redshift. 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 Amazon Redshift MCP in Google ADK

Use the McpToolset class in your ADK project to point to the server URL. Your agent gains the ability to query your data warehouse as soon as the toolset is passed to the agent.

You can restrict the agent by passing a list of allowed tool names to the McpToolset. This prevents the agent from running destructive queries if you only want read-only access.

Gemini models integrated with this MCP Server can process massive result sets. The agent acts on the data returned by `get_results` to answer complex questions about your infrastructure.

The `statement_status` tool provides the error details returned by the Redshift Data API. Your agent can catch these errors and potentially retry or report the failure.

The data transit occurs over a secure, ephemeral connection managed by Vinkius. We never store your warehouse credentials, and only the results of your specific queries leave the cluster.

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