The Apple Health MCP Server is a robust tool for managing, searching, and analyzing Apple Health data from XML exports through natural language queries and LLM-based agents.
Core Capabilities:
Data Import & Indexing: Efficiently imports and parses Apple Health XML exports, indexing them into Elasticsearch for scalable storage and retrieval
Natural Language Querying: Interact with health data using natural language prompts without needing to know underlying data formats or Elasticsearch queries
Advanced Search & Filtering: Perform flexible searches using parameters like date ranges, value ranges, record types, and source devices
Statistical Analysis & Trends: Generate comprehensive statistics (min, max, average, sum) and analyze temporal trends with daily, weekly, monthly, or yearly aggregations
Data Summaries: Provide overviews of all indexed data with total record counts and breakdowns by record types and data sources
XML Analysis Tools: Analyze raw XML structure, search XML content directly, and extract type-specific records
LLM Integration: Built on FastMCP framework for seamless integration with MCP clients like Claude Desktop
Docker Support: Container-ready for easy deployment and scaling with extensive configuration via environment variables
Processes Apple Health data exported from iPhones, enabling search, analysis, and management of personal health records, workouts, and other health metrics.
Indexes and searches Apple Health data, providing advanced querying, filtering, and aggregation capabilities for efficient health data analytics and trend analysis.
Parses and analyzes Apple Health XML exports, extracting structured health data for search, filtering, and statistical analysis.
Connect your Apple Health data with any LLM that supports MCP. Talk to your data and get personalised insights.
π‘ Demo
This demo shows how Claude uses the apple-health-mcp-server
to answer questions about your data. Example prompts from the demo:
I would like 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 of it there is.
What can you tell me about my activity in the last week? How did my daily statistics look?
Please also summarise my running workouts in July and June. Do you see anything interesting?
https://github.com/user-attachments/assets/93ddbfb9-6da9-42c1-9872-815abce7e918
Want to try it out? π Getting Started
π Why to use Apple Health MCP Server?
π§© Fit your data everywhere: using this software you can import data exported from Apple devices into any DBMS, base importer is already prepared for extensions
π― Simplify complex data access: you don't need to know data structure or use any structured query language, like SQL, simple access is just granted with natural language
ποΈ Find hidden trends: use LLM as a gate to flexible auto-generated queries which will be able to find data trends not so easy to detect manually
β¨ Key Features
π FastMCP Framework: Built on FastMCP for high-performance MCP server capabilities
π Apple Health Data Exploration: Import, parse, and analyze Apple Health XML exports
π Powerful Search & Filtering: Query and filter health records using natural language and advanced parameters
π¦ Elasticsearch, ClickHouse or DuckDB Integration: Index and search health data efficiently at scale
π οΈ Modular MCP Tools: Tools for structure analysis, record search, type-based extraction, and more
π Data Summaries & Trends: Generate statistics and trend analyses from your health data
π³ Container Ready: Docker support for easy deployment and scaling
π§ Configurable: Extensive
.env
-based configuration options
π Documentation
π Getting Started - Complete setup guide
π About - Detailed description & architecture
π§ Configuration - Environment variables and settings
π οΈ MCP Tools - All available tools
πΊοΈ Roadmap - Upcoming features and roadmap
Need help? Looking for guidance on use cases or implementation? Don't hesitate to ask your question in our GitHub discussion forum! You'll also find interesting use cases, tips, and community insights there.
π₯ Contributors
πΌ About Momentum
This project is part of Momentumβs open-source ecosystem, where we make healthcare technology more secure, interoperable, and AI-ready. Our goal is to help HealthTech teams adopt standards such as FHIR safely and efficiently. We are healthcare AI development experts, recognized by FT1000, Deloitte Fast 50, and Forbes for building scalable, HIPAA-compliant solutions that power next-generation healthcare innovation.
π Want to learn from our experience? Read our insights β themomentum.ai/blog. Interested? Let's talk!
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
Tools
A Model Context Protocol server that enables seamless interaction between LLM-based agents and Apple Health data, allowing users to query, analyze, and manage health records through natural language commands.
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