How to Use the Refiner MCP in Google ADK

Q: Can I filter which Refiner tools Google ADK exposes?

Yes. Use the toolnames filter during initialization to limit the agent's access to only the specific tools you want it to use.

Connect Refiner to Google ADK to process user feedback alongside your BigQuery data.

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Connect Refiner MCP to Google ADK

Create your Vinkius account to connect Refiner 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 Refiner with Google ADK

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Survey your SaaS users within Google ADK

Run `list_refiner_surveys` to fetch your current in-app micro-surveys. The model uses this context to decide which feedback questions to prioritize for the current user session. After deciding, the agent calls `list_refiner_responses` to fetch existing feedback. It then combines this with your BigQuery data to generate a complete view of the user.

Sync user segments using Google ADK

Fetch current user groupings with `list_refiner_segments` to tailor your agent's tone. This ensures your communication matches the user's current lifecycle stage. Updates are pushed back via `identify_refiner_user` to ensure your segment data stays fresh. The agent handles these updates as part of its standard reasoning loop.

Track interaction events in Google ADK

Use `track_refiner_event` to report actions taken by the agent back to your feedback platform. This keeps your churn signals accurate based on the agent's actual performance. Check the system health with `check_refiner_status` before starting complex workflows. This prevents the agent from attempting tasks if the feedback infrastructure is currently unavailable.

Setup guide

Set up Refiner 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 Refiner 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="Refiner_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Refiner tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Refiner MCP in Google ADK

Use the McpToolset class provided by the framework. Pass your Vinkius server URL to the params and inject it into your LlmAgent toolset list.

Absolutely. You can feed large volumes of survey response data into the agent, and it will keep the context across the entire interaction.

Yes. Use the tool_names filter during initialization to limit the agent's access to only the specific tools you want it to use.

The server supports both transport methods. Most production setups on Vinkius use the HTTP transport for better scalability across your Google Cloud infrastructure.

All survey responses and contact information are processed in memory within your secure agent environment. We do not log or store the specific PII that flows through the tool calls.

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