Apple Health MCP Server
Apple Health XML exports parsed for conversational data analysis and trend discovery.
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Overview
Apple Health MCP Server enables AI models to interact with exported Apple Health XML data. By importing your health records, the server allows you to use natural language to query personal activity, workout summaries, and daily statistics directly through your LLM interface. The tool is designed for users who wish to identify trends within their fitness and wellness data without needing to write custom SQL queries. It leverages the FastMCP framework to translate complex health data structures into a format that AI assistants can parse and analyze efficiently.
Our verdict
With a security score of 45/100, this tool carries a high risk level. A primary concern is that every installation provides full write access, and the server lacks a dedicated read-only mode to prevent unintended data modification. Furthermore, it is a community-maintained project without official vendor backing or editorial review. It is recommended only for users comfortable with self-hosting experimental, unofficial code on sensitive health data.
- Uses the FastMCP framework for high-performance server operation
- Zero direct dependencies reduces the potential software supply-chain surface
- Allows natural language querying of complex Apple Health XML data
- No read-only mode, providing full write access by default
- Community-maintained with no official vendor support or security review
- Requires manual XML exports instead of direct device synchronization
Tools
| Tool | Description | Risk |
|---|---|---|
| get_xml_structure | Analyze the structure and metadata of your Apple Health XML export (file size, tags, types). | low |
| search_xml_content | Search for specific content in the XML file (by attribute value, device, type, etc.). | low |
| get_xml_by_type | Extract all records of a specific health record type from the XML file. | low |
| get_health_summary_es | Get a summary of all Apple Health data in Elasticsearch (total count, type breakdown, etc.). | low |
| search_health_records_es | Flexible search for health records in Elasticsearch with advanced filtering and query options. | low |
| get_statistics_by_type_es | Get comprehensive statistics (count, min, max, avg, sum) for a specific health record type. | low |
| get_trend_data_es | Analyze trends for a health record type over time (daily, weekly, monthly, yearly aggregations). | low |
| search_values_es | Search for records with exactly matching values (including text). | low |
| get_health_summary_ch | Get a summary of all Apple Health data in ClickHouse (total count, type breakdown, etc.). | low |
| search_health_records_ch | Flexible search for health records in ClickHouse with advanced filtering and query options. | low |
Compatibility
| Client | Local | Docker | Remote | Read-only |
|---|---|---|---|---|
| Claude Desktop | ||||
| Cursor | ||||
| VS Code | ||||
| Windsurf | ||||
| ChatGPT |
Frequently asked questions
›Does this server still receive active development?
The project has evolved into Open Wearables, a platform for unifying wearable health data that also provides an MCP server and a companion app for continuous data sync.
›How does this server handle Apple Health data?
The server imports, parses, and analyzes XML exports generated from Apple devices.
›Which databases are supported for indexing health data?
The server supports integration with Elasticsearch, ClickHouse, and DuckDB to index and search your health records at scale.
›Is Docker supported for this server?
Yes, the server is container-ready and includes support for Docker deployment.
›How do I configure the server?
The server uses environment variables defined in a .env file for its configuration settings.
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