mdx-code 0.1.0

AI-Native Engineering Companion. Built for builders. Designed for regulated environments.

MDx Code

AI-Native Engineering Companion

Built for builders. Designed for regulated environments.

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The Story

I've been thinking about AI-powered development tools for over a year. Then I read an article that broke down Claude Code from first principles and realized something: the core architecture is embarrassingly simple.

while task_not_complete:
    response = ask_llm(conversation)
    if response.wants_tool:
        result = execute_tool(response.tool)
        conversation.append(result)
    if response.done:
        break

That's it. AI thinks → acts → observes → repeats.

Everything else is just tooling and governance wrapped around this loop.

So I built my own. Not because Claude Code isn't good... it's excellent. But because I needed something that:

• Works in regulated environments → Financial services, healthcare, government
• Owns the orchestration layer → Swap models without rewriting everything
• Respects governance rules → Audit trails, permission controls, compliance profiles
• Learns over time → The security agent gets smarter with use

MDx Code is that tool.

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Quick Start

Option 1: Install directly from GitHub (recommended)

pip install git+https://github.com/dhotherm/mdx-code.git

Option 2: Clone and install locally

git clone https://github.com/dhotherm/mdx-code.git
cd mdx-code
pip install -e .

Then authenticate and run:

# Authenticate with Claude
mdxcode auth claude

# Initialize in your project
cd your-project
mdxcode init

# Run it
mdxcode main "Fix the bug in auth.py"

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What It Does

Give it a task. Watch it work.

mdxcode "Add input validation to the user registration endpoint"

MDx Code will:

1. Read your MDXCODE.md for project context
2. Find the relevant files
3. Understand the existing patterns
4. Make changes incrementally
5. Run tests to verify
6. Log everything for audit

Scan for vulnerabilities:

mdxcode security scan

Auto-fix issues:

mdxcode security fix --auto-fix

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MDXCODE.md

Every project gets a context file. This is how MDx Code understands your project before touching anything.

# MDXCODE.md

## Project
- **Name:** Claims Processing API
- **Domain:** Health
- **Team:** Health Platform

## Conventions
- All endpoints require JWT auth
- Use Pydantic for request/response models
- Event sourcing for state changes

## Compliance
- PHI fields use SL-encrypt utility
- Never log PHI in plain text

## Guardrails
- ❌ Never commit directly to main
- ❌ Never modify production configs
- ⚠️ Schema changes require approval

Different domains, different rules. The context file captures all of that.

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Regulatory Profiles

MDx Code ships with profiles for regulated industries:

Profile	Description
standard	Default. Sensible permissions for most projects.
financial_services	Stricter controls for OSFI/SOX compliance.
healthcare	HIPAA-aware. Extra protection for PHI.
government	Maximum restrictions. Minimal auto-approval.

mdxcode "Update the API" --profile financial_services

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Multi-Model Support

Own the orchestration. Swap the models.

mdxcode "Fix the bug" --model claude    # Default
mdxcode "Fix the bug" --model gpt       # OpenAI
mdxcode "Fix the bug" --model bedrock   # AWS Bedrock

Today it's Claude. Tomorrow it could be anything. Your choice.

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Security Agent

Not just a linter. An AI that understands context.

# Scan for vulnerabilities
mdxcode security scan

# Scan specific path
mdxcode security scan --path src/

# Auto-fix what can be fixed
mdxcode security fix --auto-fix

# Teach it new patterns
mdxcode security learn

The knowledge base grows as you use it. Every fix teaches it something new.

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Audit Trail

Every action. Every decision. Logged.

~/.mdxcode/audit/2026-01-09_abc123.jsonl

{
  "timestamp": "2026-01-09T14:32:15Z",
  "event": "tool_use",
  "tool": "write_file",
  "input": {"path": "src/api.py", "content": "..."},
  "approved_by": "user",
  "session_id": "abc123"
}

Essential for compliance. Essential for trust.

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Project Structure

mdx-code/
├── mdxcode.py          # CLI entry point
├── core/
│   ├── agent_loop.py   # The heart of it
│   ├── context_loader.py
│   └── session.py
├── tools/
│   └── registry.py     # read, write, edit, bash, grep, glob
├── models/
│   ├── router.py       # Multi-model support
│   └── auth.py         # Credential management
├── governance/
│   ├── permissions.py  # What's allowed
│   ├── audit.py        # Logging everything
│   └── security_agent.py
├── knowledge/
│   └── vulnerabilities/
└── examples/
    └── demo_project/

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Philosophy

Own the orchestration layer.

Models will come and go. Vendors will compete on capability and cost. But the orchestration... the context engineering, the governance, the institutional knowledge... that's yours.

Built for regulated environments.

This isn't a toy. It's designed for environments where compliance matters, where audit trails are required, where "move fast and break things" gets you fired.

Learn over time.

The security agent grows smarter. The patterns library expands. Every project teaches it something new.

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Contributing

Found a bug? Want to add a feature? PRs welcome.

The code is intentionally readable. If you can't understand it in an afternoon, I've failed.

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License

MIT. Use it. Modify it. Build on it.

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Author

Built by MD.

Not because I had to. Because I couldn't stop thinking about it.

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"The future of software development is agents that can actually do things. Now we know how they work."