How to Use the Health XML Export Parser MCP in Google ADK

Q: How do I integrate the Health XML Export Parser with Google ADK?

Install google-adk using pip. Initialize an MCP toolset using StreamableHttpServerParameters with your Vinkius URL, then pass it to your LlmAgent via the tools parameter.

Q: Can the Health XML Export Parser and Google ADK process local files?

Yes. You provide the absolute file path to the parsehealthexport tool. Ensure the environment running the agent has read access to that specific directory.

Feed massive health histories into your Google ADK enterprise agents without hitting memory limits.

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Connect Health XML Export Parser MCP to Google ADK

Create your Vinkius account to connect Health XML Export Parser 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 Health XML Export Parser with Google ADK

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Big Data Parsing for Google ADK

The `parse_health_export` tool fixes the bloated nature of Google Fit and Apple Health exports by streaming the file from disk. Standard Python XML libraries build a DOM tree in memory, which crashes on 500MB+ files. Your Google ADK agents can now process multi-gigabyte health histories without crashing. The tool aggregates the raw XML tags into clean, actionable metrics like daily step counts and average heart rates. Even with Gemini's massive 1M+ token context window, feeding it condensed data is faster and significantly cheaper than sending raw XML.

Enterprise Cloud Integration

Your Google ADK agents use the `parse_health_export` tool via this MCP Server to extract health metrics directly on Google Cloud. The agent triggers the tool to pull the data, which it can then route straight into BigQuery for long-term storage or Vertex AI for predictive modeling. You only need one endpoint token to authenticate. The server handles the complex parsing logic off-site, freeing up your local compute resources for actual data analysis.

Targeted Tool Exposure

You use the `tool_names` filter in your setup to explicitly expose only the `parse_health_export` tool to your agent. When configuring the toolset, you define exactly what your agent is allowed to execute. This prevents the agent from hallucinating actions or attempting to use unrelated tools. It focuses the model entirely on extracting and aggregating the health metrics you requested.

Setup guide

Set up Health XML Export Parser 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 Health XML Export Parser 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="Health XML Export Parser_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Health XML Export Parser tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Health XML Export Parser MCP in Google ADK

Install `google-adk` using pip. Initialize an MCP toolset using `StreamableHttpServerParameters` with your Vinkius URL, then pass it to your `LlmAgent` via the `tools` parameter.

Standard libraries build a DOM tree in memory, which crashes on 500MB+ health exports. This MCP Server uses a streaming parser to pull metrics sequentially without consuming massive RAM.

Yes. You provide the absolute file path to the `parse_health_export` tool. Ensure the environment running the agent has read access to that specific directory.

Absolutely. As long as you are using the Google ADK framework, the underlying Gemini or Vertex AI model can invoke the parsing tool.

The MCP integration processes your Apple Health and Google Fit XML data within a strict V8 Isolate Sandbox. The environment is completely stateless, meaning no historical health metrics are retained after the connection closes.

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