mcp-server-dexcom-health
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
- Time window queries - Query specific time ranges (e.g., "4-3 hours ago")
- 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 with optional time windows | | 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-health
# Using pip
pip install mcp-server-dexcom-healthConfiguration
Set environment variables:
| Variable | Required | Description | |----------|----------|-------------| | DEXCOM_USERNAME | Yes | Dexcom username, email, or phone (+1234567890) | | 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: ``json { "mcpServers": { "dexcom": { "command": "uvx", "args": ["mcp-server-dexcom-health"], "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"
"What about the hour before that?" (follow-up queries work!)
Time Window Queries
Query specific time ranges using start_minutes and end_minutes:
# Last 3 hours (standard)
get_glucose_readings(minutes=180)
# Specific window: 4 hours ago to 3 hours ago
get_glucose_readings(start_minutes=240, end_minutes=180)
# Stats for 6-5 hours ago
get_statistics(start_minutes=360, end_minutes=300)
# Episodes between 8-4 hours ago
detect_episodes(start_minutes=480, end_minutes=240)Supported tools: get_glucose_readings, get_statistics, detect_episodes, export_data
Persistence Layer Integration
Tools that analyze data accept an optional data parameter for external data sources: ```python
Pass your own historical data
result = get_statistics( data=[ {"glucose_mg_dl": 120, "timestamp": "2024-01-15T08:00:00Z"}, {"glucose_mg_dl": 135, "timestamp": "2024-01-15T08:05:00Z"},
... 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
