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PAIML MCP Agent Toolkit (pmat)
Zero-configuration AI context generation system with extreme quality enforcement and Toyota Way standards. Analyze any codebase instantly through CLI, MCP, or HTTP interfaces. Built by Pragmatic AI Labs.
π― v2.88.0 Release: Technical Debt Grading (TDG) System! Complete code quality scoring with 6 orthogonal metrics:
- π Comprehensive Scoring: Structural complexity, semantic complexity, code duplication, coupling analysis
- π Documentation Coverage: Language-specific documentation pattern detection and scoring
- π¨ Consistency Analysis: Naming conventions, indentation patterns, and code style consistency
- π Grade Classification: A+ through F grading system with detailed component breakdowns
- π Multi-Language Support: 10+ languages including Rust, Python, JavaScript, TypeScript, Go, Java, C/C++
- π οΈ CLI & MCP Integration:
pmat analyze tdgcommand and MCP tools for programmatic access- π Project Analysis: Directory-level analysis with language distribution and aggregated scoring
π v2.10.0: Claude Code Agent Mode - "Always Working" Achievement! Transform PMAT into a persistent background quality agent:
- π€ Claude Code Integration: Native MCP server for seamless Claude Code integration
- πΎ Persistent State: Monitoring state maintained across restarts with auto-save
- βοΈ Production Ready: Environment-specific configs for dev, prod, and CI/CD
- π Real-time Monitoring: Continuous quality tracking with file system watching
- ποΈ Service Architecture: Systemd deployment with health checks and auto-restart
π― v2.9.0: Universal Demo "Just Works" Achievement! Complete AI-powered repository intelligence with multi-language analysis:
- π€ AI-Powered Recommendations: Framework-aware repository recommendations with complexity-based learning tiers
- π Multi-Language Intelligence: Advanced polyglot analysis with cross-language dependency detection
- ποΈ Architecture Pattern Recognition: Microservices, Layered, Event-driven pattern detection with confidence scoring
- π Repository Showcase Gallery: Curated collection of 8+ repositories across languages and complexity levels
- β‘ Universal Demo: Any GitHub repository URL β Complete analysis with AI recommendations
- π Enhanced Web Demo: Interactive visualizations with 3 new API endpoints (/api/recommendations, /api/polyglot, /api/showcase)
- Toyota Way Excellence: Zero compilation defects maintained throughout development
π Quick Start
Installation
Choose your preferred installation method - PMAT is available across all major package ecosystems:
π¦ Rust (Recommended)
π¦ Package Managers
# macOS/Linux - Homebrew
# Windows - Chocolatey
# Ubuntu/Debian - APT
# Arch Linux - AUR
# Node.js - npm (global)
π³ Docker
# Latest version
# Interactive analysis
π§ From Source
π₯ Direct Download
# Linux/macOS Quick Install
|
# Windows PowerShell
# Download from: https://github.com/paiml/paiml-mcp-agent-toolkit/releases
Basic Usage
# Analyze current directory
# Technical Debt Grading (TDG) - NEW!
# Get complexity metrics
# Find technical debt
# Run quality gates
# Start MCP server
Universal Demo - "Just Works" Analysis
# Analyze any GitHub repository with AI recommendations
# Compare multiple repositories across languages
# Run quality gates on GitHub repositories
# Start interactive web demo
# Then visit http://localhost:8080 for:
# β’ AI-powered repository recommendations
# β’ Multi-language project intelligence
# β’ Repository showcase gallery
# β’ Interactive analysis visualizations
Toyota Way Development (NEW)
# Setup quality enforcement (one-time)
# Start development with quality checks
# Create quality-enforced commit
# Verify sprint quality
π― Core Capabilities
Analysis Engine
- Technical Debt Grading (TDG): 6-metric orthogonal code quality scoring with A+ through F grading
- Complexity Analysis: McCabe cyclomatic & cognitive complexity with AST precision
- Dead Code Detection: Graph-based reachability analysis across 30+ languages
- SATD Detection: Self-admitted technical debt with severity classification
- Documentation Coverage: Language-specific pattern detection with scoring algorithms
- Consistency Analysis: Naming conventions and code style consistency measurement
- Deep Context Generation: Multi-dimensional analysis optimized for AI agents
π€ AI-Powered Intelligence (NEW)
- Smart Recommendations: Framework-aware repository suggestions with complexity matching
- Polyglot Analysis: Cross-language dependency detection and architecture pattern recognition
- Repository Showcase: Curated gallery with learning pathways from beginner to expert
- Integration Points: Risk assessment of multi-language project coupling with mitigation strategies
Quality Systems
- Quality Gates: Zero-tolerance enforcement (complexity β€20, SATD=0, coverage >80%)
- Quality Proxy: AI code interceptor with 7-stage validation pipeline
- PDMT Integration: Deterministic todo generation with embedded quality requirements
- Refactoring Engine: State machine-based code transformation with ACID snapshots
ποΈ Agent System (Enterprise)
- Distributed Architecture: Actix actor system with zero-copy messaging and Raft consensus
- Sub-Agent Types: AnalyzerActor, TransformerActor, ValidatorActor, OrchestratorActor
- Workflow Engine: DSL-based automation with step dependencies and parallel execution
- Resource Management: CPU/Memory/GPU/Network/IO control with enterprise-grade fault tolerance
- MCP Integration: Full Model Context Protocol server with multiple transport modes
Integration Protocols
- MCP Protocol: 18 tools via unified pmcp SDK 1.2.0 server (includes TDG analysis tools)
- HTTP API: RESTful with Server-Sent Events streaming
- CLI Interface: 47 commands with POSIX-compliant exit semantics
π Documentation
Core Documentation
- Complete Specification - Unified source of truth (36 sections)
- TDG Guide - NEW! Technical Debt Grading system documentation
- Agent Architecture - NEW! Sub-agent system and distributed computing capabilities
- API Reference - Service APIs and integration patterns
- CLI Reference - Complete command documentation
Quality & Development
- Toyota Way Guide - Development workflow and standards
- Sprint Management - Task tracking and execution DAG
- Quality Gates - Enforcement mechanisms
Integration Guides
- MCP Integration - Model Context Protocol setup
- PDMT Guide - Deterministic todo generation
- CI/CD Integration - Pipeline integration
ποΈ Architecture
PMAT implements Toyota Production System principles through rigorous static analysis:
- Kaizen (ζΉε): Iterative file-by-file improvement with measurable ΞQ metrics
- Genchi Genbutsu (ηΎε°ηΎη©): Direct AST traversal, no heuristics
- Jidoka (θͺεε): Automated quality gates with fail-fast semantics
- Zero SATD Policy: Compile-time enforcement of zero technical debt
Service Architecture
// Unified service layer with dependency injection
// All protocols use unified request/response
Performance Characteristics
- Startup: 4ms hot, 127ms cold (mmap'd grammar cache)
- Analysis: 487K LOC/s single-thread, 3.9M LOC/s multi-core
- Memory: 47MB base + 312KB per KLOC
- SIMD: 43% vectorized paths, 2.7x AVX2 speedup
π οΈ Development
Requirements
- Rust 1.80.0+
- Git (for repository analysis)
Build from Source
# Setup Toyota Way quality enforcement
# Build and test
# Run examples
Library Usage
[]
= "2.88.0"
use CodeAnalysisService;
async
π Language Support
- Rust: Full cargo integration with syn AST
- TypeScript/JavaScript: SWC-based parsing
- Python: RustPython AST analysis
- C/C++: Tree-sitter with goto tracking
- Ruchy: v1.5.0 support with advanced analysis
- Full AST parsing with 35+ token types
- Halstead metrics (volume, difficulty, effort, time, bugs)
- Dead code detection (unused functions/variables)
- Type inference for literals and binary operations
- Actor message flow analysis with deadlock detection
- Enhanced pattern matching complexity scoring
- Import/export dependency tracking
- Kotlin: Tree-sitter based analysis
- 30+ Languages: Via tree-sitter grammar support
π€ MCP Integration
PMAT provides 18 MCP tools via unified pmcp SDK server:
# Start MCP server (auto-detects transport)
# Test with Claude Code
Available Tools
analyze_tdg- NEW! Technical Debt Grading with 6-metric scoringanalyze_tdg_compare- NEW! Compare TDG scores between files/projectsanalyze_complexity- Complexity metricsanalyze_satd- Technical debt detectionanalyze_dead_code- Unused code analysisquality_gate- Comprehensive quality validationrefactor_start- Begin refactoring workflowpdmt_deterministic_todos- Generate quality todosgithub_create_issue- Create GitHub issues- NEW: AI recommendation tools for intelligent repository analysis
- And 9 more...
π€ Claude Code Agent Mode (NEW v2.10.0)
Transform PMAT into a persistent background quality agent that continuously monitors your codebase:
Quick Start with Claude Code
# Start agent as MCP server for Claude Code
# Configure in Claude Code settings.json:
{
}
Background Daemon Mode
# Start monitoring a project
# Check monitoring status
# Stop monitoring
Key Features
- Real-time Monitoring: File system watching with instant quality feedback
- Persistent State: Maintains metrics across restarts with auto-save
- Toyota Way Compliance: Enforces β€20 complexity with zero SATD tolerance
- Production Ready: Systemd service with health checks and auto-restart
- MCP Native: Seamless Claude Code integration via stdio transport
Available Agent Tools
start_quality_monitoring- Begin monitoring a projectstop_quality_monitoring- Stop monitoringget_quality_status- Current quality metricsrun_quality_gates- Execute quality checksanalyze_complexity- Complexity analysishealth_check- Agent health status
See Claude Code Agent Guide for detailed setup and deployment instructions.
π Web Demo API Endpoints (NEW)
# AI-powered repository recommendations
# Multi-language project intelligence
# Repository showcase gallery
# Core analysis APIs
π Quality Standards
PMAT enforces extreme quality standards:
- Complexity: β€20 cyclomatic, β€15 cognitive
- Technical Debt: 0 SATD comments allowed
- Test Coverage: >80% with property-based testing
- Code Quality: 0 lint warnings, 0 dead code
- Documentation: Synchronized with every commit
Quality Gates
# Run comprehensive quality analysis
# CI/CD integration
π Contributing
PMAT follows Toyota Way development principles:
- Setup quality enforcement:
make setup-quality - Start development:
make dev - Make changes with documentation updates
- Quality-enforced commit:
make commit - Sprint verification:
make sprint-close
All contributions must meet:
- Zero SATD comments
- Complexity β€20 per function
- Full test coverage
- Documentation updates
Contribution guidelines coming soon.
π License
Licensed under the MIT License.
Built with β€οΈ by Pragmatic AI Labs