monix 0.2.1

Gemini-powered terminal assistant for server monitoring

Monix

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Overview

Monix is a terminal-native, read-only AI assistant for server monitoring. It pairs a slash-command CLI with a Gemini-backed conversational agent so operators can inspect CPU, memory, disk, processes, services, logs (plain files, Nginx, Docker), and webhook alerts without leaving the shell — and without ever issuing destructive commands.

• Two interfaces, one mental model — fast /slash commands for known intents, natural-language chat for everything else. Both share the same underlying tools.
• Zero runtime dependencies — standard library only (urllib, json, inspect, subprocess, …).
• Cross-platform — Linux (procfs) and macOS (vm_stat / sysctl).

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Quick Start

Install

pip install monix

On Ubuntu/Debian, use pipx to avoid the externally-managed-environment error:

sudo apt install pipx && pipx install monix && pipx ensurepath && source ~/.bashrc

With MCP server support:

pip install "monix[mcp]"
# or
pipx install "monix[mcp]"

Launch the interactive REPL

monix

On first launch, Monix prompts for a Gemini API key (paste-friendly, hidden input). The key is saved to ~/.monix/keystore and never asked again. Skip with Enter to run in local-only mode.

One-shot mode

monix /stat cpu
monix /log /var/log/syslog 100
monix "why is memory so high?"

MCP server

monix-mcp

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Configuration

Gemini API Key

On first launch, Monix automatically prompts for a key. You can also run setup explicitly:

monix --setup

Or set it via environment variable:

export GEMINI_API_KEY="AIza..."

Get a free key at Google AI Studio.

Environment Variables

Variable	Description	Default
GEMINI_API_KEY	Gemini API key (required for AI features)	—
MONIX_MODEL	Gemini model to use	gemini-2.5-flash
MONIX_LOG_FILE	Default log file path	auto-detected
MONIX_CPU_WARN	CPU alert threshold (%)	85.0
MONIX_MEM_WARN	Memory alert threshold (%)	85.0
MONIX_DISK_WARN	Disk alert threshold (%)	90.0
MONIX_DISCORD_WEBHOOK	Discord webhook URL	—
MONIX_SLACK_WEBHOOK	Slack webhook URL	—
MONIX_NOTIFY_COOLDOWN	Alert cooldown (seconds)	3600
MONIX_NOTIFY_CPU	Enable CPU alerts (0/false to disable)	1
MONIX_NOTIFY_MEM	Enable memory alerts	1
MONIX_NOTIFY_DISK	Enable disk alerts	1
MONIX_PLATFORM	Override platform detection (linux/mac)	auto

.env in the current working directory is automatically loaded.

Webhook Alerts (in-app)

Webhooks can also be configured without leaving the shell:

/notify set discord https://discord.com/api/webhooks/...
/notify set slack https://hooks.slack.com/services/...
/notify status

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Examples

> /stat cpu
  CPU 23.4%   load 0.41 / 0.38 / 0.30

> /log @api --search timeout
  [3 matches in last 500 lines]
  2026-04-26 12:14:02  ERROR  upstream timeout (10s) on /v1/orders
  ...

> show me containers using the most memory
  → tool: list_containers
  → tool: ... (correlates with snapshot)
  Top container by RSS is `payments-api` (1.2 GB / 2 GB cap).
  Recent restarts: 0.  Suggested follow-up: /docker logs payments-api

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Slash Commands

Snapshots and live monitoring

Command	Purpose
/stat [cpu|memory|disk|swap|net|io|all]	Current snapshot, or /stat cpu 24h for collected history
/watch [metric] [sec]	Real-time refreshing dashboard (Ctrl-C to stop)
/cpu /memory /disk /swap /net /io	Single-metric shortcuts
/top [N]	Top-N processes by CPU

Logs

Command	Purpose
/log add @alias -app <path>	Register an application log under an alias
/log add @alias -nginx <path>	Register an Nginx log
/log add @alias -docker <name>	Register a Docker container log
/log list	Show all registered aliases
/log @alias [-n N]	Tail a registered log
/log @alias --search [pattern]	Filter for errors / a regex pattern
/log @alias --live	Stream live
/log /path [-n N] [--live]	Direct path access (no registration)
/log remove @alias	Unregister
/logs <path> [N]	One-shot tail (legacy form)

Docker

Command	Purpose
/docker ps	List running containers
/docker add @alias <name>	Register a container alias
/docker @alias [-n N] [--search] [--live]	Tail / search / stream
/docker logs|search|live <name>	Direct (no alias)
/docker remove @alias	Unregister

Notifications

Command	Purpose
/notify test [discord|slack]	Send a test alert to the configured webhook; sends to both if omitted
/notify status	Show webhook configuration, cooldown, metric toggles, and last sent state
/notify help	Show notification command and environment variable reference

Services and AI

Command	Purpose
/service <name>	systemd service status
/ask <question>	Force routing to Gemini
/clear	Clear current conversation history
/help	Show full command reference
/exit	Quit

Background metrics collector

Command	Purpose
/collect set <interval> <retention> <folder>	Start periodic snapshot collection (e.g. 1h 30d ./metrics)
/collect list	Show config and run state
/collect remove	Disable and delete config

Webhook alert configuration

Monix can format threshold alerts for Discord and Slack webhooks. Repeated identical alerts are rate-limited with a local state file at ~/.monix/notify_state.json.

export MONIX_DISCORD_WEBHOOK="https://discord.com/api/webhooks/..."
export MONIX_SLACK_WEBHOOK="https://hooks.slack.com/services/..."
export MONIX_NOTIFY_COOLDOWN=3600

# Per-metric notification toggles. Use 0, false, or no to disable.
export MONIX_NOTIFY_CPU=1
export MONIX_NOTIFY_MEM=1
export MONIX_NOTIFY_DISK=1

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Agent Conversation (Multi-Turn Internals)

Monix's conversational mode is a two-dimensional multi-turn loop, implemented in monix/core/assistant.py and monix/llm/.

Dimension	Meaning	State
A. Conversation turns	Successive user prompts, each carrying prior context	Caller-owned history: list[dict], accumulated across REPL turns
B. Tool-calling rounds	Within one user prompt, the model may call tools repeatedly before answering	Loop inside answer() — bounded by _MAX_TOOL_ROUNDS = 5

Per-prompt loop

1. Take a fresh snapshot (CPU/mem/disk/processes/alerts) and
   append it, plus the registered log alias table, to the user
   text — gives the model a current "world view" up front.

2. Send working history + tool schemas → Gemini.

3. Inspect response parts:
     • text only          → terminal state, append (user, model)
                            to caller history and return.
     • functionCall(s)    → execute each via call_tool(),
                            append the model candidate (verbatim,
                            preserving thought_signature) and the
                            functionResponse parts to the working
                            history, then loop.

4. After 5 rounds the loop exits with a tools-disabled summary
   call so the model is forced to answer with what it already saw.