How to Use the Health XML Export Parser MCP in OpenAI Agents SDK

Q: How do I connect the Health XML Export Parser to the OpenAI Agents SDK?

Install openai-agents via pip. Create an MCPServerStreamableHttp instance with your MCP endpoint URL. Pass it into the mcpservers array in your Agent constructor.

Q: Can the Health XML Export Parser and OpenAI Agents SDK handle 2GB export files?

Yes. The parsehealthexport tool streams the file from disk rather than loading it entirely into memory. It aggregates the data so the agent only receives the condensed metrics.

Q: Does the OpenAI Agents SDK cache the Health XML Export Parser tools?

You can set cacheToolsList=True in your server configuration. This speeds up initialization by skipping the auto-discovery phase on subsequent runs.

Parse gigabyte-scale Apple Health and Google Fit XML exports directly within your OpenAI Agents SDK workflows.

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Connect Health XML Export Parser MCP to OpenAI Agents SDK

Create your Vinkius account to connect Health XML Export Parser to OpenAI Agents SDK 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 OpenAI Agents SDK

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Stream Massive Files via MCP Server

The `parse_health_export` tool processes gigabyte-scale Apple Health and Google Fit XML exports directly within your OpenAI Agents SDK workflows. It uses a streaming parser to read elements sequentially. Your agent won't hit memory limits or context window overflows, even when analyzing years of historical health metrics. You pass the absolute file path to the tool. It aggregates the raw data into actionable metrics before handing it back to your agent. This keeps the token count manageable while preserving the core health insights.

Production-Grade Guardrails

When your agent decides to run the `parse_health_export` tool, OpenAI Agents SDK provides built-in validation before executing the operation. These guardrails ensure the file path is formatted correctly and accessible on the host machine before any parsing begins. Because this is an MCP integration, you can track every parsing operation through the OpenAI dashboard. Full tracing lets you monitor how long the parser took, what parameters the agent passed, and exactly which metrics the XML returned.

Agent Handoffs for Health Data

You can build specialized agents that specifically run the `parse_health_export` tool to pull step counts and heart rates. This extraction agent handles the initial file processing and aggregates the raw XML tags into clean JSON. Once the data is aggregated, that agent hands the context off to an analysis agent. This keeps your system modular and prevents any single agent from getting bogged down by the initial file parsing mechanics.

Setup guide

Set up Health XML Export Parser MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Health XML Export Parser tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Health XML Export Parser tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Health XML Export Parser tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Health XML Export Parser Agent",
            instructions="You have access to Health XML Export Parser tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Health XML Export Parser MCP in OpenAI Agents SDK

Install `openai-agents` via pip. Create an `MCPServerStreamableHttp` instance with your MCP endpoint URL. Pass it into the `mcp_servers` array in your Agent constructor.

Yes. The `parse_health_export` tool streams the file from disk rather than loading it entirely into memory. It aggregates the data so the agent only receives the condensed metrics.

You can set `cacheToolsList=True` in your server configuration. This speeds up initialization by skipping the auto-discovery phase on subsequent runs.

It pulls actionable data like step counts, heart rates, and active energy burned. The tool condenses these from the raw XML tags into a format your agent can actually read.

Vinkius runs this MCP integration inside an ephemeral V8 Isolate Sandbox. Your Apple Health and Google Fit XML files are processed in a zero-trust environment that destroys all data the second the parsing finishes.

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