AI Project OS MCP

AI Project OS MCP

Enforces engineering governance for AI-driven software projects, ensuring state over prompt, freeze over generate, and audit over output through the 5S workflow.

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README

AI Project OS

PyPI Version License Python Versions

AI Project Operating System
Turn AI coding into real, auditable software engineering.

Quick Start

Installation

pip install ai-project-os-mcp

Usage

  1. Initialize a new project:

    ai-project-os init my-project
    cd my-project
    
  2. Start with S1 Scope stage:

    ai-project-os s1
    
  3. Follow the 5S workflow:

    # After completing S1, move to S2
    ai-project-os s2
    
    # Then S3, S4, and finally S5
    ai-project-os s3
    ai-project-os s4
    ai-project-os s5
    
  4. Check project status:

    ai-project-os status
    

For Non-Technical Users

If you don't want to use the command line, check out our Zero-Code Guide to use AI Project OS with just your AI tool.

Status

⚠️ AI Project OS v2.5 is currently in Spec-Frozen / Implementation-in-Progress state.

  • Architecture and module design are frozen
  • Core governance engine implementation is ongoing
  • APIs, modules, and governance behaviors may change until v2.5.0 release
  • Not yet suitable for production use

For stable v1.x version, please check the v1 branch.

What is this?

AI Project OS is an engineering-grade operating system for AI-driven software projects.

It does not try to make AI "smarter".
It makes AI obedient to real-world engineering rules.

AI Project OS enforces:

  • Clear project stages
  • Frozen decisions
  • Guarded code generation
  • Mandatory audit trails

No freeze, no code.
No audit, no ship.

What AI Project OS is NOT

  • ❌ Not an AI code quality checker
  • ❌ Not responsible for business logic correctness
  • ❌ Not a replacement for human review

Why AI Project OS?

AI coding fails in real projects because:

  • AI skips steps
  • AI rewrites architecture
  • AI patches instead of redesigning
  • Humans cannot tell when AI crossed the line

AI Project OS fixes this by introducing engineering governance.

Core Concepts

1. State over Prompt

Project truth lives in state.json, not in conversation memory.

2. Freeze over Generate

All decisions must be frozen before execution.

3. Audit over Output

Code without audit is not considered done.

The 5S Workflow

Stage Meaning Code Allowed
S1 Scope
S2 Spec
S3 Structure
S4 Schedule
S5 Ship

MCP-Based Governance

AI Project OS is implemented as a Model Context Protocol (MCP) server.

This allows:

  • Claude
  • Cursor
  • Trae
  • Local agents

To act as governed engineering executors, not free-form chatbots.

S5 Stability Guard (Mandatory)

Every S5 task must include:

  • Context Refresh
  • Change Fuse
  • Pseudo-TDD
  • Audit Record

No exception.

Approval Field

Approval MUST be provided by a human reviewer. In audit logs:

  • AI may suggest content
  • Human reviewer must explicitly sign off

AI self-approval is forbidden for compliance reasons.

Who is this for?

  • Non-technical founders
  • Product managers using AI coding
  • Teams tired of AI-generated mess
  • Anyone who wants AI to behave like a real engineer

License

MIT License

MCP Server Runtime Modes

Mode Usage Security Features
STDIO Claude / Cursor / Trae Lightweight, for development
HTTP Dashboard / Enterprise Supports authentication, for production

Core Principle

拒绝违规执行 比勉强完成任务更正确

AI Project OS believes that refusing to execute violations is more correct than勉强 completing tasks.

Version Semantics

We follow Semantic Versioning:

  • MAJOR (x.0.0): Governance model or MCP protocol changes
  • MINOR (1.x.0): New governance capabilities, backward compatible
  • PATCH (1.0.x): Bug fixes, documentation, or non-behavioral changes

Release & Rollback Policy

  • Release: Git tags trigger GitHub Actions for automatic PyPI publishing
  • Rollback: Never delete published versions, only release fix versions (e.g., v1.0.1)

LTS Support

v2.5.x will maintain backward compatibility for governance schemas.

Enterprise Edition Roadmap

The following capabilities are reserved for future enterprise editions:

  • Multi-project isolation
  • Centralized audit logging
  • Private MCP Registry
  • SSO / RBAC support

Philosophy

AI should not be creative about structure.
AI should be creative only within frozen boundaries.

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