Now in Beta
Model the Context.
Enforce the Outcome.
Enforce the Outcome.
Stop guessing with prompts. Use the MMC Workbench to build governed roadmaps for your AI — ensuring every execution is deterministic, version-controlled, and audit-ready.
Live SKILL.md example
Finance ApprovalSKILL.md
Active
When this happens
trigger: "invoice > $10,000"
owner: "finance-team"
owner: "finance-team"
Your rules are enforced
- require_approval: CFO
- notify: slack://finance-alerts
- log_to: xero://audit-trail
- notify: slack://finance-alerts
- log_to: xero://audit-trail
CFO notified via Slack · Xero audit logged · Jira ticket raised — automatically, every time
The Problem
AI that guesses isn't good enough
for real business rules.
Most AI rollouts fail not because the AI is bad — but because "write a prompt and hope" isn't a governance strategy.
When your business depends on specific rules — finance sign-offs, security checks, multi-team approvals — inconsistency has real consequences.
Your AI guesses the process
Prompts drift. Different users get different results. Nobody knows what the AI will do next time.
Nothing is auditable
When something breaks you can't trace why. No version history. No defence in a compliance review.
Your logic is locked in someone else's system
Switching AI providers means starting from scratch. Your business rules belong to a vendor, not you.
MMC replaces guesswork with defined, auditable rules.
Deterministic logic. Version-controlled in your GitHub. Executed by an open-source engine you own and can audit.
How It Works
From process document
to governed execution.
Three steps that turn your existing process documents into auditable, automated business skills.
1
Model
Map your rules in the Workbench
A visual blueprint of your business logic — no coding required
Import your existing process documents and use the Workbench's visual Outcome Modeling canvas to define exactly how your business works — which team owns which decision, what triggers an escalation, where one workflow ends and another begins. The Workbench guides you step by step.
2
Commit
Push your logic to your own GitHub
Your rules, your repository — MMC never stores your data
MMC translates your model into a SKILL.md file and commits it to your own GitHub repository. Every change is versioned, reviewable, and reversible. Your GitHub becomes the single source of truth — auditable by your team, your auditors, and your AI agents.
3
Execute
Deploy governed skills via open-source MCP
Your AI follows the rules reliably — and you can prove it
Your AI agent — Claude, Gemini, or any MCP-compatible model — connects to the open-source MMC MCP Server. It reads the rules directly from your repository and enforces them through secure connectors to Xero, Slack, Jira, and GitHub. Every execution is traceable.
Why MMC is Different
The old way vs
the governed way.
FAQ
Questions we get asked.
If something isn't clear after reading this page, it's our fault not yours.
Do I need to be technical to use MMC?+
No. If you can describe a business process in plain language, you can use MMC.
The Workbench guides you through Outcome Modeling visually. You're defining your business rules, not writing code. The SKILL.md output is generated for you automatically and committed to your GitHub without any command-line knowledge needed.
Why does my logic need to go to GitHub?+
Because it means you own it — with a full history of every change, forever.
GitHub gives you version control, access control, and a complete audit trail at enterprise scale. Every update to your business rules is tracked, attributable, and reversible. Your security team already trusts GitHub — MMC just uses it as the storage layer so there's no new system to approve.
Is the MCP Server genuinely open source?+
Yes. Fork it, audit it, self-host it — it will always be free and open.
The execution engine is a public standard. You can inspect every line, run it on your own infrastructure, and never depend on MMC staying in business for your AI agent to keep working. The Workbench is our premium IDE for authoring and managing skills — the server is yours.
Which AI agents does it work with?+
Claude and Gemini natively, plus any MCP-compatible agent.
MMC is purpose-built as the authoring environment for SKILL.md files — the same format Claude uses for skill execution. Skills are model-agnostic by design: the same SKILL.md file that runs on Claude today will run on any future MCP-compatible agent without modification.
Free to start · Open source at the core · No database required
Give your AI agents
rules they can't ignore.
Join the teams turning process documents into governed, automated execution — without losing ownership of their logic.
Works with Claude, Gemini & any MCP-compatible agent · Your GitHub, your data