mcp-server-dexcom-health 0.1.0

MCP server for Dexcom CGM glucose data - continuous health intelligence for AI agents

mcp-server-dexcom

MCP server for Dexcom CGM glucose data. Enables AI agents to access and analyze continuous glucose monitor data for health intelligence applications.

Features

• Real-time glucose monitoring - Current readings with trend analysis
• Historical data access - Up to 24 hours of glucose history
• Clinical analytics - Time-in-range, GMI, CV%, AGP reports
• Episode detection - Automatic hypo/hyper event identification with detailed context
• Time-block analysis - Identify patterns by time of day
• Persistence layer support - Pass external data for long-term analysis

Tools

Tool	Description
get_current_glucose	Current glucose reading with trend
get_glucose_readings	Historical readings (up to 24h)
get_statistics	TIR, CV%, GMI, and other metrics
get_status_summary	Complete "how am I doing?" summary
detect_episodes	Find hypo/hyper episodes
get_episode_details	Deep analysis of each episode
analyze_time_blocks	Patterns by time of day
check_alerts	Real-time threshold alerts
export_data	Export for external storage
get_agp_report	Clinical AGP report

Installation

# Using uvx (recommended)
uvx mcp-server-dexcom

# Using pip
pip install mcp-server-dexcom

Configuration

Set environment variables:

Variable	Required	Description
DEXCOM_USERNAME	Yes	Dexcom username, email, or phone [phone])
DEXCOM_PASSWORD	Yes	Dexcom password
DEXCOM_REGION	No	us (default), ous (outside US), or jp (Japan)

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "dexcom": {
      "command": "uvx",
      "args": ["mcp-server-dexcom"],
      "env": {
        "DEXCOM_USERNAME": "your_username",
        "DEXCOM_PASSWORD": "your_password",
        "DEXCOM_REGION": "us"
      }
    }
  }
}

Usage Examples

Basic usage with Claude

"What's my current glucose?"

"How was my overnight control?"

"Did I have any lows today?"

"Give me my statistics for the last 12 hours"

Persistence Layer Integration

Tools that analyze data accept an optional data parameter for external data sources:

# Pass your own historical data
result = get_statistics(
    data=[
        {"glucose_mg_dl": 120, "timestamp": "2024-01-15T08:00:00"},
        {"glucose_mg_dl": 135, "timestamp": "2024-01-15T08:05:00"},
        # ... more readings
    ]
)

This enables building long-term analytics by storing data externally and passing it back for analysis.

Requirements

• Python 3.10+
• Active Dexcom Share session (requires Dexcom mobile app with Share enabled)
• At least one follower configured in Dexcom Share

License

MIT

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## **3. Create `LICENSE`:**

MIT License

Copyright (c) 2024

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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## **4. Create `.gitignore`:**

pycache/ *.py[cod] *$py.class .env .venv/ dist/ build/ *.egg-info/ .mypy_cache/ .ruff_cache/

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## **5. Final project structure:**

mcp-server-dexcom/ ├── pyproject.toml ├── README.md ├── LICENSE ├── .gitignore ├── .env # (not committed) └── src/ └── mcp_server_dexcom/ ├── init.py └── server.py