How to Use the Breathing Timer MCP in Google ADK

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Connect Breathing Timer MCP to Google ADK

Create your Vinkius account to connect Breathing Timer 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 Breathing Timer with Google ADK

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Generating Schedules for Google ADK

Use `generate_breathing_schedule` to create full, structured breathing routines. The agent calculates schedules based on a total duration, allowing you to map out complex intervention paths in your enterprise systems. Since this MCP Server runs inside Vinkius, your long-context Gemini model can trust the output. It guarantees that the scheduling logic is sound before feeding it into BigQuery for analysis.

Checking Parameters with Google ADK

Need to verify timing details? The `query_breathing_parameters` tool retrieves default cycle settings for Box Breathing or 4-7-8. It’s a simple, direct query that keeps your agent focused on precise data. You can integrate this into your LlmAgent flow, letting the model act as a protocol validator before performing any critical actions.

Measuring Cycle Time with Google ADK

When an agent needs to know the exact length of one cycle, it calls `calculate_single_cycle_duration`. This function figures out the precise total duration for a given breathing technique. This level of precision is vital when building enterprise agents that need to interact with detailed health records in BigQuery.

Setup guide

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

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Common questions about Breathing Timer MCP in Google ADK

It provides structured cycles and accurate timing data. Your agent can use this MCP Server to validate scheduling logic, ensuring the entire process is medically sound.

Yes. The core mechanisms are designed for reliability and accuracy. You can pass results from this MCP Server into your BigQuery data sets easily.

This server touches breathing cycle metadata, including structured timing parameters and adherence logs. All interactions are managed via a zero-trust proxy, ensuring your keys never sit on disk.

It handles standard techniques like Box Breathing, 4-7-8, and Coherence Heart Rate. The tools are designed to be flexible for various health protocols.

Yes. You can chain this MCP Server capability with other toolsets, letting your LlmAgent build automations that span multiple functional areas.

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