user-db

user-db

Central user-state database MCP server with durable profile facts and live virtual sensors (stress, room intensity) with configurable smoothing, readable by any agent or smart-home service.

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README

user-db

Central user-state database as an MCP server: durable profile facts plus live virtual sensors (user stress level, room intensity) with configurable smoothing — readable in real time by any agent or smart-home service.

Data separation (important)

This repository contains software only. All personal data lives outside the repo, in the directory given by USER_DB_DIR (default ~/.config/user-db/):

File Content Written by
profile.json durable user facts (name, speech id, birthday, profession, expertise, traits, ...) you / agents via profile_set
config.json sensor + curve configuration (reactiveness tuning) you
state.json live sensor state this software

Nothing in this repo ever contains user data; examples/ holds neutral templates. Copy them to USER_DB_DIR to get started:

mkdir -p ~/.config/user-db
cp examples/*.json ~/.config/user-db/

Install & run

python3 -m venv .venv && .venv/bin/pip install mcp
claude mcp add --scope user user-db -- $PWD/.venv/bin/python $PWD/server.py

CLI (same core, for shell loops and Home Assistant command_line sensors):

bin/userdb profile
bin/userdb sensor report stress 70
bin/userdb sensor read stress
bin/userdb state

MCP tools

  • profile_get / profile_set(field, value) — the user's durable state.
  • sensor_read(name) / sensor_report(name, value) — virtual sensors.
  • state_get — all sensors + the curve combining both axes.

Virtual sensors & reactiveness

A sensor value is not a plain variable. Producers report raw observations (0–100); the stored value follows them via time-aware exponential smoothing:

alpha = 1 - exp(-dt / tau_seconds)
value += alpha * (raw - value)

tau_seconds per sensor in config.json is the reactiveness: small tau = reactive, large tau = inert. This keeps the sensor from jumping and lets you fine-tune it for smart-home automations. The first report initialises the value directly.

Default sensors: stress (the user's stress level, reported by a watchdog/perception agent) and room_intensity (the room's current scene intensity, reported by a scene-analysis agent — see docs/neuronal-interceptor.md).

The two axes & the curve

The system has two orthogonal axes: user stress and room intensity. A freely definable piecewise-linear curve in config.json maps stress to a target room intensity:

"curve": {"x": "stress", "y": "room_intensity",
          "points": [[0, 85], [40, 60], [70, 35], [100, 15]]}

state_get evaluates it and returns target and delta (actual − target) — the basis for smart-home decisions ("the user is stressed but the room is loud → calm it down").

Home Assistant

Expose the smoothed value as a command_line sensor, or bridge it through an existing MCP that already abstracts Home Assistant:

sensor:
  - platform: command_line
    name: user_stress
    command: "/path/to/user-db/bin/userdb sensor read stress | jq .value"
    scan_interval: 60

License

MIT

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