How to Use the GetFeedback MCP in Google ADK

Q: How do I configure GetFeedback inside Google ADK?

Install google-adk and wrap your endpoint URL in StreamableHttpServerParameters. Pass that into McpToolset and assign it to your LlmAgent tools array to link the MCP Server.

Q: Can Google ADK trigger GetFeedback emails?

Yes, by default. The agent can invoke sendsurveyinvites unless you explicitly exclude it using the tool filter.

Q: Does GetFeedback work with Gemini 1.5 Pro via Google ADK?

Yes. You can dump the entire output of listsurveys into the 1M+ token window. The model analyzes the exact wording of every question across your entire account.

Q: How do I monitor API consumption?

Your agent runs checkapilimits before executing large batch pulls. You can pipe these metrics directly into Google Cloud Monitoring.

Q: How does the MCP Server protect my GetFeedback respondents?

Personally identifiable text from getresponsedetails processes entirely within an ephemeral container. Vinkius drops the environment the moment your Google Cloud agent finishes execution, leaving zero residual trace of user identities.

Feed GetFeedback survey data directly into your Google ADK agents to run long-context sentiment analysis on massive datasets.

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Connect GetFeedback MCP to Google ADK

Create your Vinkius account to connect GetFeedback 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 GetFeedback with Google ADK

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Google ADK Context Ingestion

Calling `list_survey_responses` through this MCP Server dumps thousands of GetFeedback customer entries straight into Gemini's massive context window. You don't need to chunk the text. The agent reads the entire history of a product line in one pass. Once the data is in memory, your agent cross-references it with BigQuery tables. It uses `get_survey_details` to match campaign IDs against Google Cloud revenue metrics for immediate ROI calculations.

Automated BigQuery Pipelines

Enterprise pipelines rely on `list_completed_feedback` to filter out abandoned GetFeedback forms before ingestion. Your agent pulls only the finalized answers and structures them for Vertex AI processing. You configure the MCP toolset to expose specific tools. If you only want the agent reading data, you restrict access to `send_survey_invites` entirely using the optional `tool_names` filter.

Large-Scale Pagination

Agents handling historical GetFeedback data use `list_feedback_page` to walk through years of survey records. They write the output directly to Google Cloud Storage buckets as they go. Connection drops won't break your pipeline. The framework periodically runs `verify_api_connection` to ensure the endpoint is alive before starting a massive batch job.

Setup guide

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

Install `google-adk` and wrap your endpoint URL in `StreamableHttpServerParameters`. Pass that into `McpToolset` and assign it to your `LlmAgent` tools array to link the MCP Server.

Yes, by default. The agent can invoke `send_survey_invites` unless you explicitly exclude it using the tool filter.

Yes. You can dump the entire output of `list_surveys` into the 1M+ token window. The model analyzes the exact wording of every question across your entire account.

Your agent runs `check_api_limits` before executing large batch pulls. You can pipe these metrics directly into Google Cloud Monitoring.

Personally identifiable text from `get_response_details` processes entirely within an ephemeral container. Vinkius drops the environment the moment your Google Cloud agent finishes execution, leaving zero residual trace of user identities.

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