SciTeX Notification (scitex-notification)

Multi-backend notification system — give your AI agents a voice

Full Documentation · pip install scitex-notification

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Interfaces: Python ⭐⭐⭐ (primary) · CLI ⭐⭐ · MCP ⭐⭐ · Skills ⭐⭐ · Hook — · HTTP —

Problem and Solution

#	Problem	Solution
1	Ad-hoc alerting zoo — smtplib.sendmail, requests.post(slack_webhook, …), plyer.notify, twilio.rest.Client, print + beep all demand different APIs, env vars, and error handling	One call, nine backends — stxn.alert("done") routes across audio TTS, desktop, emacs, matplotlib, playwright, email, webhook, Telegram, and Twilio with a unified signature
2	Silent failures waste hours — a webhook 500s or SMTP is down and the agent never tells you, so you stare at the terminal "just in case"	Automatic fallback chain — default order audio → emacs → matplotlib → playwright → email; first live backend wins, and level-based routing escalates critical to phone/SMS
3	AI agents have no voice — long-running jobs and overnight training finish unnoticed; you can't leave your desk or sleep through a run	Escalation to phone/SMS — stxn.call() / stxn.sms() via Twilio wake you for critical events; audio TTS covers the room, Telegram / webhook covers everyone else

Problem

Developers delegate tasks to AI coding agents — and then wait. Staring at terminals wastes time and drains cognitive resources. Sitting for hours waiting for results takes a physical toll, too.

Solution

SciTeX Notification lets you leave your desk — or even sleep — while your agents keep working. One MCP server gives them a voice in the following channels: TTS, phone calls, SMS, email, and webhooks.

Supported Backends

Backend	API	Transport	Cost	Internet	Notes
Audio	alert()	TTS to local speakers	Free	No	Via scitex-audio; SSH relay supported
Desktop	alert()	notify-send / PowerShell	Free	No	Linux / WSL
Emacs	alert()	emacsclient message	Free	No	Popup, minibuffer, or alert
Matplotlib	alert()	Visual popup window	Free	No
Playwright	alert()	Browser popup	Free	No
Email	alert()	SMTP	Free	Required	Gmail, SMTP relay
Webhook	alert()	HTTP POST	Free	Required	Slack, Discord, custom endpoints
Twilio	call() sms()	Phone call / SMS	Paid	Required	Twilio setup needed

alert() tries backends in fallback order until one succeeds. call() and sms() target Twilio directly.

Auditory Feedback -> Phone Call Escalation

When an AI agent needs your attention — even while you sleep — it can escalate from audio to phone call.

   

Fig. 1: Left — Claude Code terminal showing audio → phone call escalation after 7 consecutive auditory feedback but with no response from the user. Right — iPhone receiving repeated "SciTeX Alert" calls from the AI agent.

Penetrating iPhone Silent Mode:

1. Emergency Bypass (most reliable): Save your Twilio number as a contact → Ringtone → enable Emergency Bypass. All calls ring regardless of Focus/Silent mode.
2. Repeated Calls (fallback): iOS allows the second call from the same number within 3 minutes to ring through. repeat=2 triggers this automatically with a 30-second gap.

Example Command for Claude Code (`/speak-and-continue`)

The /speak-and-continue command is a real-world example of scitex-notification in action. It configures an AI coding agent (Claude Code) to:

1. Provide TTS feedback via audio_speak MCP tool while working autonomously
2. Repeat the same audio message when the user sends /speak-and-continue again (they may be away)
3. Count consecutive speaks without user response (spoke counter)
4. Escalate to phone call after 7 unanswered speaks — waking the user if asleep

This enables a 24/7 development workflow: the agent works autonomously, speaks progress aloud, and calls your phone when it needs your attention or when all tasks are complete.

Installation

Requires Python >= 3.10.

pip install scitex-notification

Install with optional backends:

pip install "scitex-notification[audio]"    # audio alerts via scitex-audio
pip install "scitex-notification[twilio]"   # SMS via Twilio
pip install "scitex-notification[mcp]"      # MCP server for AI agents
pip install "scitex-notification[all]"      # everything

Quickstart

Python API

import scitex_notification as notification

notification.alert("Job done")                           # default backend (with fallback)
notification.alert("Error", backend="email")             # specific backend
notification.alert("Critical", backend=["sms", "email"]) # multiple backends
notification.call("Urgent!")                             # phone call via Twilio
notification.sms("Build done!")                          # SMS via Twilio
notification.available_backends()                        # list installed backends

Full API reference

CLI Commands

scitex-notification --help                       # Show all commands
scitex-notification send "Job done"              # Send via default backend
scitex-notification send "Done" --backend email  # Send via specific backend
scitex-notification config                       # Show configuration
scitex-notification backends                     # List available backends
scitex-notification mcp list-tools              # List MCP tools

Full CLI reference

MCP Server — for AI Agents

AI agents can send notifications and check system status autonomously.

Tool	Description
notify_handler	Send an alert via specified or fallback backends
notify_by_level_handler	Send alert using level-based backend config
list_backends_handler	List all backends with availability status
get_config_handler	Show current notification configuration

scitex-notification mcp start

Full MCP specification

Setup

Environmental Variables List .env.example.

MCP Server

For AI Agents such as Claude Code.

Example

Add .mcp.json to your project root. Use SCITEX_NOTIFICATION_ENV_SRC to load all configuration from a .src file — this keeps .mcp.json static across environments:

{
  "mcpServers": {
    "scitex-notification": {
      "command": "scitex-notification",
      "args": ["mcp", "start"],
      "env": {
        "SCITEX_NOTIFICATION_DEFAULT_BACKEND": "audio",
        "SCITEX_NOTIFICATION_TWILIO_SID": "ACxxxxxxx",
        "SCITEX_NOTIFICATION_TWILIO_TOKEN": "...",
        "SCITEX_NOTIFICATION_TWILIO_TO": "+XX-XXX-XXX-XXXX",
        "SCITEX_AUDIO_RELAY_PORT": "${SCITEX_AUDIO_RELAY_PORT}"
      }
    }
  }
}

Speakers Centralization

Remote machines can speak from your local speakers.

Setup example can be seen at ./docs/audio-relay-setup.src

Example

1. Local machine (has speakers) — start the relay server:

scitex-audio relay start --port 31293

2. SSH config (~/.ssh/config) — forward the relay port:

Host my-server
    HostName 192.168.x.x
    RemoteForward 31293 127.0.0.1:31293

3. Remote server — audio plays on your local speakers:

import scitex_notification as notify
notify.alert("Training complete. Val loss: 0.042")

4. Shell profile (optional) — auto-configure per host:

# ~/.bashrc.d/audio.src (sourced via SCITEX_AUDIO_ENV_SRC)
export SCITEX_AUDIO_RELAY_PORT=31293

# Local machine: run relay server
if [[ "$(hostname)" == "my-laptop" ]]; then
    export SCITEX_AUDIO_MODE=local
    scitex-audio relay start --port $SCITEX_AUDIO_RELAY_PORT &>/dev/null &
fi

# Remote server: use relay via SSH tunnel
if [[ "$(hostname)" == "my-server" ]]; then
    export SCITEX_AUDIO_MODE=remote
fi

Twilio for Phone Call and SMS

Example

export SCITEX_NOTIFICATION_DEFAULT_BACKEND=audio
export SCITEX_NOTIFICATION_TWILIO_SID=ACxxxxxxx
export SCITEX_NOTIFICATION_TWILIO_TOKEN=...
export SCITEX_NOTIFICATION_TWILIO_TO=+XX-XXX-XXX-XXXX

Part of SciTeX

SciTeX Notification is part of SciTeX.

The SciTeX system follows the Four Freedoms for Research below, inspired by the Free Software Definition:

Four Freedoms for Research

0. The freedom to run your research anywhere — your machine, your terms.
1. The freedom to study how every step works — from raw data to final manuscript.
2. The freedom to redistribute your workflows, not just your papers.
3. The freedom to modify any module and share improvements with the community.

AGPL-3.0 — because we believe research infrastructure deserves the same freedoms as the software it runs on.

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