TrueV1sion/SixSigmaMCP

Six Sigma Model Context Protocol (MCP)

🚀 Overview

A complete implementation of Six Sigma DMAIC methodology as a Model Context Protocol (MCP) server for Claude Desktop. This enables AI-assisted software development with built-in quality controls and systematic process improvement.

🆕 Version 2.0 - Enhanced with Subagent Integration

NEW: The enhanced version (enhanced-six-sigma-server.js) integrates Claude's specialized subagents to provide:

• Real performance metrics instead of templates
• Actual bug detection with stack traces
• Working code improvements not just recommendations
• Live monitoring setup with real dashboards

See for details on the subagent-powered version.

✅ Current Status

Fully Implemented and Working! The core Six Sigma MCP server is now complete with all DMAIC phases operational.

🎯 Key Features

DMAIC Phase Implementation

• Define: Voice of Customer (VOC) analysis, CTQ tree generation, constraint documentation, SIPOC diagrams
• Measure: KPI definition, baseline establishment, Measurement System Analysis (MSA)
• Analyze: Root Cause Analysis (RCA), Failure Mode Effects Analysis (FMEA), statistical analysis
• Improve: Solution generation, evaluation, and implementation planning
• Control: Control plans, monitoring setup, validation, and documentation

Quality Management

• Phase Gate Criteria: Automated checking of phase completion requirements
• Quality Scoring: Real-time quality metrics throughout the project
• Risk Assessment: FMEA-based risk level calculation
• Progress Tracking: Complete project status visibility

📁 Project Structure

SixSigmaMCP/
├── mcp-server/
│   ├── six-sigma-server.js    # Main MCP server (COMPLETE)
│   ├── package.json           # Dependencies
│   └── [legacy test files]    # Previous debugging attempts
├── protocol/
│   └── six_sigma_mcp_protocol.dsx    # Protocol specification
├── implementation/
│   └── agents/                # Future multi-agent implementation
├── CONFIG_INSTRUCTIONS.md     # Setup instructions
└── README.md                  # This file

🔧 Installation

1. Prerequisites:

   • Node.js 14+ installed
   • Claude Desktop application

2. Install Dependencies:

   cd C:\Users\jared\OneDrive\Desktop\SixSigmaMCP\mcp-server
   npm install @modelcontextprotocol/sdk
   

3. Configure Claude Desktop: Add to your claude_desktop_config.json:

   "six-sigma-mcp": {
     "command": "node",
     "args": [
       "C:/Users/jared/OneDrive/Desktop/SixSigmaMCP/mcp-server/six-sigma-server.js"
     ],
     "env": {}
   }
   

4. Restart Claude Desktop

💡 Usage Examples

Creating a New Project

User: Create a Six Sigma project for a high-performance API

Claude: I'll create a Six Sigma project for your high-performance API using the DMAIC methodology.

[Creates project with requirements, budget, and timeline]

Running DMAIC Phases

User: Execute the define phase for project proj_1234567

Claude: I'll execute the Define phase to analyze customer requirements and establish quality criteria.

[Performs VOC analysis, generates CTQ tree, documents constraints, creates SIPOC]

Checking Progress

User: Show me the project status

Claude: [Displays current phase, completion percentage, quality score, and phase status]

🏗️ Architecture

Single Server Implementation

The current implementation uses a single, comprehensive MCP server that handles all DMAIC phases. This provides:

• Simplified deployment
• Centralized state management
• Consistent phase transitions
• Integrated quality gates

Phase Components

Define Phase

• VOC Analysis: Categorizes requirements into functional/non-functional
• CTQ Tree: Maps customer needs to measurable quality characteristics
• Constraints: Documents technical, business, and regulatory constraints
• SIPOC: Creates Supplier-Input-Process-Output-Customer diagram

Measure Phase

• KPI Definition: Establishes measurable metrics for each CTQ
• Baseline Establishment: Captures current performance levels
• MSA: Validates measurement system reliability

Analyze Phase

• Root Cause Analysis: Identifies underlying issues
• FMEA: Evaluates failure modes and calculates Risk Priority Numbers
• Statistical Analysis: Calculates process capability and sigma levels
• Gap Analysis: Quantifies improvement opportunities

Improve Phase

• Solution Generation: Creates solutions based on approach (incremental/redesign/innovative)
• Solution Evaluation: Scores solutions on impact, effort, risk, and cost
• Implementation Planning: Develops phased implementation timeline

Control Phase

• Control Plans: Establishes control charts and response plans
• Monitoring Setup: Configures alerts and dashboards
• Documentation: Creates SOPs and training materials
• Validation: Performs comprehensive testing

🔍 Technical Implementation

State Management

• Projects stored in memory (Map structure)
• Each project tracks:
  • Basic info (name, budget, timeline)
  • Current phase and phase status
  • Artifacts from each phase
  • Quality metrics and risk levels
  • Gate criteria completion

Quality Gates

Each phase has specific criteria that must be met:

• Automatic checking via check_phase_gate
• Clear indication of met/unmet criteria
• Prevents progression without completion

Metrics Calculation

• Quality Score: Composite of phase completion, gate criteria, and risk level
• Risk Level: Based on FMEA average RPN scores
• Phase Completion: Percentage progress through DMAIC

🚀 Future Enhancements

Multi-Agent Architecture

• Separate agents for each DMAIC phase
• Inter-agent communication via shared resources
• Specialized expertise per agent

Claude Integration

• AI-powered solution generation in Improve phase
• Intelligent requirement analysis
• Automated code quality validation

Persistence Layer

• Redis integration for state management
• Project history and analytics
• Multi-user support

Advanced Features

• Real-time dashboards
• Predictive analytics
• Integration with development tools
• Automated testing integration

🤝 Contributing

The project is structured for easy extension:

1. Core server logic in six-sigma-server.js
2. Clear separation of phase implementations
3. Modular helper functions
4. Comprehensive error handling

📝 License

This implementation is part of the Six Sigma MCP framework for AI-assisted development.

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Created by: Six Sigma AI Framework
Version: 1.0.0
Status: Production Ready