How to Use the Unleash (Feature Toggles) MCP in Google ADK

Q: How do I check flag status with Unleash (Feature Toggles) on Google ADK?

Start by invoking getclientfeatures. This tool pulls all active feature flags and strategies for server-side evaluation. The result tells your agent exactly if a feature is live or needs to be toggled off, informing your BigQuery operations.

Q: Can I list projects using Unleash (Feature Toggles) with Google ADK?

Yes. Use listprojects to get all available project IDs. After that, you can use listprojectfeatures to check flags for a given ID. This helps restrict the scope of your agent's actions.

Q: What data types are touched when I report metrics with Unleash (Feature Toggles) on Google ADK?

The metric reporting tools, reportclientmetrics and reportfrontendmetrics, track flag usage metadata. They record which features were accessed and by what client context within the MCP Server.

Q: Does the MCP Server help me list all environments for Unleash (Feature Toggles) using Google ADK?

The listenvironments tool fetches every environment configured in Unleash. Knowing this is crucial because flag status changes dramatically between development, staging, and production environments.

Q: What if I need to check flags for users? How does Unleash (Feature Toggles) work with Google ADK?

Use listusers first to get all configured user accounts. Then, pass this context into tools like getclientfeatures. This makes sure your agent evaluates the correct feature set based on the specific user.

Build enterprise agents with Unleash (Feature Toggles) using Google ADK.

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Connect Unleash (Feature Toggles) MCP to Google ADK

Create your Vinkius account to connect Unleash (Feature Toggles) 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 Unleash (Feature Toggles) with Google ADK

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Evaluate feature flags based on context.

The `get_client_features` tool fetches all active feature flags and strategies for server-side evaluation. Because you're building enterprise agents, this lets your agent make high-stakes decisions about running code paths. Need to pass more data? Use `get_frontend_features`. This provides context like user IDs or custom properties, which is essential when connecting the MCP Server to BigQuery data.

Organize and scope feature checks by project.

The agent uses `list_projects` to fetch every Unleash project ID. From there, running `list_project_features` lets your toolset focus on flags for one specific project. This granular approach keeps the reasoning clean. It ensures that when your Gemini model processes the data, it only sees the feature set relevant to the current business unit.

Track usage and performance from multiple sources.

You track flag usage with `report_client_metrics`, which sends back metrics from a backend SDK instance. You can also use `report_frontend_metrics` to log activity from the user interface. These tools ensure that every interaction is logged and measurable, keeping your enterprise MCP Server running clean.

Setup guide

Set up Unleash (Feature Toggles) 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 Unleash (Feature Toggles) 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="Unleash (Feature Toggles)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Unleash (Feature Toggles) tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Unleash (Feature Toggles) MCP in Google ADK

Start by invoking `get_client_features`. This tool pulls all active feature flags and strategies for server-side evaluation. The result tells your agent exactly if a feature is live or needs to be toggled off, informing your BigQuery operations.

Yes. Use `list_projects` to get all available project IDs. After that, you can use `list_project_features` to check flags for a given ID. This helps restrict the scope of your agent's actions.

The metric reporting tools, `report_client_metrics` and `report_frontend_metrics`, track flag usage metadata. They record which features were accessed and by what client context within the MCP Server.

The `list_environments` tool fetches every environment configured in Unleash. Knowing this is crucial because flag status changes dramatically between development, staging, and production environments.

Use `list_users` first to get all configured user accounts. Then, pass this context into tools like `get_client_features`. This makes sure your agent evaluates the correct feature set based on the specific user.

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