How to Use the Virtuagym MCP in Google ADK

Q: How do I check a member's full history using Virtuagym and Google ADK?

The agent executes searchmembers. This tool gives you the profile, membership details, and complete fitness progress data. Since it connects to BigQuery, this information is immediately available for large-scale analysis.

Q: Can I list all available classes with Virtuagym and Google ADK?

Yes. The listactivities tool provides descriptions and duration data for every class. Your agent can ingest this structured data into BigQuery for trending analysis.

Q: Does Virtuagym and Google ADK support multiple service listings?

It does. You can query listmemberships for current plans and then call listnutritionplans to get dietary options. These structured calls maintain data integrity across the board.

Scale Virtuagym operations with Google ADK. Connect your agent to BigQuery and enterprise systems.

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Connect Virtuagym MCP to Google ADK

Create your Vinkius account to connect Virtuagym 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 Virtuagym with Google ADK

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Access Member Data via MCP Server

Your agent uses `get_member` to retrieve full user profiles from within the Gemini ecosystem. This isn't just a lookup; it’s a data action that can feed into BigQuery for deeper analysis. Need more detail? The `search_members` tool gives you membership status, progress metrics, and check-in history all at once.

List Services Using Google ADK

The agent can query the club's service catalog. Use `list_activities` to get class descriptions and durations for your staff. Or, use `list_events` for upcoming special classes. Want to know what plans are available? Running `list_memberships` gives you the current offering lineup.

Manage Training Plans with Google ADK

The MCP Server lets your agent handle complex training data. It uses tools like `list_workout_plans` and `list_nutrition_plans`. This is perfect for aggregating specialized care. It also tracks who's teaching by calling `list_trainers`, which keeps the operational data accurate when building enterprise workflows.

Setup guide

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

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Common questions about Virtuagym MCP in Google ADK

The agent executes `search_members`. This tool gives you the profile, membership details, and complete fitness progress data. Since it connects to BigQuery, this information is immediately available for large-scale analysis.

Yes. The `list_activities` tool provides descriptions and duration data for every class. Your agent can ingest this structured data into BigQuery for trending analysis.

This MCP Server manages detailed member records, including fitness progress, membership status, event history, and nutrition plans. It's built to hold large volumes of operational data.

It does. You can query `list_memberships` for current plans and then call `list_nutrition_plans` to get dietary options. These structured calls maintain data integrity across the board.

The server handles member profiles, which include fitness progress metrics and check-in history. Using BigQuery means you have deep control over how this sensitive user data is stored and queried.

Use it with your favorite AI tools

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