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MCamner/README.md

Mattias Camner

CI GitHub Pages Version License: MIT

Infrastructure / Endpoint / Automation Architect

Endpoint readiness · Repo intelligence · Governed AI operations

I build reviewable tools for endpoint readiness, repository intelligence, and governed local AI operations.

Operating model: enterprise complexity becomes operational signal, scored readiness, safe automation, reviewed action, and technical memory

Run readiness tools · Journal · LinkedIn · Black Iris

Start here

I need endpoint readiness I want to understand the MQ architecture
Run the browser check for a fast, browser-visible validation. Follow the operating model from signal and score to policy gate and reusable memory.
Open Diagnostics v2 for profile-based evaluation and helper-enriched evidence. Explore macos-scripts as the terminal entrypoint to the stack.

Client readiness in practice

The public demo evaluates endpoint signals against explicit profiles, shows the evidence behind every result, and provides remediation suitable for review by support or operations.

Client Readiness Diagnostics v2 showing a sanitized IGEL and Citrix profile evaluation

Browser check or local helper?

Mode What it can inspect Best for
Browser-only Browser, secure context, display, locale, timezone, and basic endpoint reachability Fast first-line validation with no installation
Browser + read-only helper OS, network, certificates, smartcard, Citrix, management signals, and named baselines Deeper diagnostics and repeatable operational evidence

The page automatically falls back to browser-only checks when the helper is unavailable. See the helper setup and deployment guide for the standard-library-only local agent.

What I build

The MQ stack connects local repositories, endpoint operations, and AI-assisted engineering through one practical loop:

endpoint / repo / workflow
→ signal
→ score
→ gate
→ memory
→ better next action

The focus is operational: make state visible, decisions explainable, and automation safe enough to use under real pressure.

MQ ecosystem

Repository Role
macos-scripts Terminal entrypoint and local workflow toolkit
mq-agent Orchestrates sweeps, reviews, release gates, and alerts
mq-mcp Policy-bound MCP runtime for controlled tool execution
mqobsidian Single source of truth: technical memory, decisions, and exported agent context
repo-signal Scores repo readiness and exports structured AI context
mq-image-analyze Extracts operational signal from screenshots and UI states
mq-ums Provides a gated operator surface for IGEL UMS workflows

Explore the full MQ ecosystem

Operating model

MQ operating architecture

One entrypoint, layered workflows, reviewable actions.

The model favors signal before action, local execution, explicit policy gates, and reusable technical memory. Read the operating model.

More project notes · Security and public-data policy

Connect

Technical journal · LinkedIn · Black Iris

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  1. macos-scripts macos-scripts Public

    A modular CLI for structured terminal workflows, automation, and system tools on macOS.

    Shell 2

  2. mq-agent mq-agent Public

    Terminal-native AI agent orchestrator with safety gates, repo intelligence, and controlled execution workflows.

    Python 1

  3. mq-mcp mq-mcp Public

    Deterministic MCP runtime for safe tool execution, policy gates, contracts, and local AI workflow governance.

    Python 1

  4. mqobsidian mqobsidian Public

    Architecture memory layer for MQ-stack truth exports, repo reviews, decisions, learning records, and operational knowledge.

    Python 2

  5. repo-signal repo-signal Public

    Repo intelligence engine for readiness scoring, release gates, and AI-context exports.

    Python 1

  6. excalidraw-ai-proxy excalidraw-ai-proxy Public

    Server-side proxy for Excalidraw AI requests that keeps the OpenAI API key on the server.

    JavaScript 1