Apple Health MCP Server is an open-source project designed to let users interact with Apple Health data through natural language. It runs as an MCP (Model Context Protocol) server and can connect to any MCP-enabled LLM, enabling users to "converse with their data" and obtain personalized insights.
In terms of purpose, the project is mainly used to import, parse, and analyze Apple Health XML export data. It can import data exported from Apple devices into any database management system (DBMS), and the base importer is ready for extension. Users do not need to understand the data structure or use structured query languages such as SQL; they can access the data using natural language alone. The project can also use an LLM as an entry point to discover data trends that are difficult to detect manually through flexibly auto-generated queries.
Key capabilities include: built on the FastMCP framework, providing high-performance MCP server capabilities; support for Apple Health data exploration, with the ability to import, parse, and analyze XML export files; powerful search and filtering features, allowing health records to be queried and filtered using natural language and advanced parameters; integration with Elasticsearch, ClickHouse, or DuckDB to efficiently index and search health data at scale; modular MCP tools for structural analysis, record search, type-based extraction, and more; generation of data summaries and trends, producing statistical and trend analysis from health data; support for Docker containerized deployment for easy scaling; and rich .env-based configuration options.
In terms of usage, users need to connect an MCP-enabled LLM and then query the data through natural language prompts. Example prompts include: "I want you to help me analyze my Apple Health data. Let's start by analyzing the data types—check what data is available and how much there is." "Can you tell me about my activity last week? What do my daily stats look like?" "Please summarize my running workouts in July and June. Do you see anything interesting?" The project provides complete documentation including a getting started guide, About (detailed description and architecture), Configuration (environment variables and settings), MCP Tools (all available tools), and a roadmap. If users have questions, they can ask in the GitHub discussion forum, where there are also interesting use cases, tips, and community insights.
The applicable scenarios are mainly personal health data analysis, especially for users who own Apple devicesand want to explore their own health data in depth. It is also suitable for HealthTech teams to adopt standards such as FHIR securely and efficiently. The project is part of the Momentum open-source ecosystem. Momentum is an expert in healthcare AI development, has been recognized by FT1000, Deloitte Fast 50, and Forbes, and focuses on building scalable, HIPAA-compliant solutions.
In terms of limitations, the current materials do not explicitly list specific limitations. However, note that the project originally relied on manual XML exports and has now evolved into Open Wearables—a self-hosted platform that unifies wearable health data from multiple devices (including Apple Health). Open Wearables also provides an MCP server and companion app for continuous Apple Health data synchronization, thereby eliminating the need for manual XML exports. To learn more, visit github.com/the-momentum/open-wearables.
