apeiron-mcp

An MCP server exposing client health data. Tool surface is intentionally consolidated by data shape (time-series vitals, periodic assessments, unstructured text, derived aggregates) rather than by raw domain, to keep LLM tool-selection unambiguous.

Tools

#	Tool	Purpose
1	`get_sleep_data`	Sleep stages, duration, efficiency, HRV, score.
2	`get_exercise_data`	Workouts: type, duration, calories, HR zones, RPE.
3	`get_nutrition_data`	Meals, macros, calories, hydration, supplements.
4	`get_cardio_metrics`	Cardio + aerobic (resting HR, HRV, VO2max, BP, aerobic capacity).
5	`get_fitness_assessment`	Bone density, body comp, balance, movement, muscle strength.
6	`get_cognitive_data`	Cognitive test batteries and trends.
7	`get_healthspan_domain_summary`	Cross-domain rolled-up scores.
8	`get_lifestyle_summary`	Sleep/activity/nutrition adherence rollup.
9	`get_trends`	Generic time-series trend for any (domain, metric).
10	`get_notes`	Clinician/client/system free-text notes.
11	`get_chat_history`	Paginated coaching conversation logs.

All tools return the envelope:

{
  "client_id": "...",
  "domain": "...",
  "period": {"start": "...", "end": "..."},
  "data": [],
  "unit_system": "metric",
  "last_synced_at": "..."
}

Install & run

pip install -e .
apeiron-mcp            # runs the server over stdio

Register with Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "apeiron": {
      "command": "apeiron-mcp"
    }
  }
}

Wiring to a real backend

The current implementation returns stub payloads. Replace the bodies of the functions in src/apeiron_mcp/server.py with calls into your health data backend (HTTP client, DB, etc.).