Docs & Usage Guide

PAIML MCP Agent Toolkit (pmat)

Name: PAIML MCP Agent Toolkit
Author: paiml

Zero-configuration AI context generation system that analyzes any codebase instantly through CLI, MCP, or HTTP interfaces. Built by Pragmatic AI Labs with extreme quality standards and zero tolerance for technical debt.

Toyota Way Success: Achieved 97% complexity reduction in stubs.rs through complete modular refactoring (v0.29.5). Project maintains zero tolerance standards: 0 SATD comments, 0 failing doctests, 0 failing property tests, 72+ comprehensive property tests, and proper separation of concerns across all components. Latest refactoring created dedicated modules (language_analyzer.rs, defect_formatter.rs, dead_code_formatter.rs) eliminating 549 lines of duplicated code while maintaining full functionality ✅

🚀 Installation

Install pmat using one of the following methods:

From Crates.io (Recommended):
```
cargo install pmat
```
With the Quick Install Script (Linux only):
```
curl -sSfL https://raw.githubusercontent.com/paiml/paiml-mcp-agent-toolkit/master/scripts/install.sh | sh
```
macOS users: Please use cargo install pmat instead. Pre-built binaries are only available for Linux.

From Source:

git clone https://github.com/paiml/paiml-mcp-agent-toolkit
cd paiml-mcp-agent-toolkit
cargo build --release

From GitHub Releases: Pre-built binaries for Linux are available on the releases page. macOS and Windows users should use cargo install pmat.

Requirements

Rust: 1.80.0 or later
Git: For repository analysis

🚀 Getting Started

Quick Start

# Analyze current directory
pmat context

# Get complexity metrics for top 10 files
pmat analyze complexity --top-files 10

# Analyze specific files with include patterns
pmat analyze complexity --include "src/*.rs" --format json

# Test with validated examples (try these!)
cargo run --example complexity_demo
pmat analyze complexity --include "server/examples/complexity_*.rs"

# Find technical debt
pmat analyze satd

# Run comprehensive quality checks
pmat quality-gate --strict

Using as a Library

Add to your Cargo.toml:

[dependencies]
pmat = "0.28.0"

Basic usage:

use pmat::{
    services::code_analysis::CodeAnalysisService,
    types::ProjectPath,
};

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let service = CodeAnalysisService::new();
    let path = ProjectPath::new(".");
    
    // Generate context
    let context = service.generate_context(path, None).await?;
    println!("Project context: {}", context);
    
    // Analyze complexity
    let complexity = service.analyze_complexity(path, Some(10)).await?;
    println!("Complexity results: {:?}", complexity);
    
    Ok(())
}

Key Features

🔍 Code Analysis

Deep Context Analysis - Comprehensive AST-based code analysis with defect prediction
Complexity Analysis - Accurate McCabe cyclomatic and cognitive complexity metrics with AST-based precision
- ✅ v0.28.6+: Fixed algorithm accuracy - now provides 100% correct complexity calculations
- Supports nested control flow, match statements, async functions, and complex branching
- Validated against manual calculations with comprehensive test examples
Dead Code Detection - Find unused code across your project
Technical Debt Gradient (TDG) - Quantify and prioritize technical debt
SATD Detection - Find Self-Admitted Technical Debt in comments
Code Duplication - Detect exact, renamed, gapped, and semantic clones

🛠️ Refactoring Tools

AI-Powered Auto Refactoring - pmat refactor auto achieves extreme quality standards
- Single File Mode - pmat refactor auto --single-file-mode --file path/to/file.rs for targeted refactoring
Documentation Cleanup - pmat refactor docs maintains Zero Tolerance Quality Standards
Interactive Refactoring - Step-by-step guided refactoring with explanations
Enforcement Mode - Enforce extreme quality standards using state machines
- Single File Mode - pmat enforce extreme --file path/to/file.rs for file-specific enforcement

📊 Quality Gates & CI/CD Integration

Lint Hotspot Analysis - Find files with highest defect density using EXTREME Clippy standards
- Single File Mode - pmat lint-hotspot --file path/to/file.rs for targeted analysis
Provability Analysis - Lightweight formal verification with property analysis
Defect Prediction - ML-based prediction of defect-prone code
Quality Enforcement - Exit with error codes for CI/CD integration
- NEW: All analyze commands now support --fail-on-violation for CI/CD pipelines
- Exit code 0 on success, 1 when violations exceed thresholds
- Perfect for GitHub Actions, GitLab CI, Jenkins, and other CI/CD systems

🔧 Language Support

Rust - Full support with cargo integration
TypeScript/JavaScript - Modern AST-based analysis
Python - Comprehensive Python 3 support
Kotlin - Memory-safe parsing with full language support
C/C++ - Tree-sitter based analysis
WebAssembly - WASM binary and text format analysis
AssemblyScript - TypeScript-like syntax for WebAssembly
Makefiles - Specialized linting and analysis

📋 Tool Usage

CLI Interface

# Zero-configuration context generation
pmat context                                    # Auto-detects language
pmat context --format json                     # JSON output
pmat context -t rust                           # Force toolchain
pmat context --skip-expensive-metrics          # Fast mode

# Code analysis
pmat analyze complexity --top-files 5         # Complexity analysis
pmat analyze complexity --fail-on-violation   # CI/CD mode - exit(1) if violations
pmat analyze churn --days 30                  # Git history analysis  
pmat analyze dag --target-nodes 25            # Dependency graph
pmat analyze dead-code --format json          # Dead code detection
pmat analyze dead-code --fail-on-violation --max-percentage 10  # CI/CD mode
pmat analyze satd --top-files 10              # Technical debt
pmat analyze satd --strict --fail-on-violation  # Zero tolerance for debt
pmat analyze deep-context --format json       # Comprehensive analysis
pmat analyze deep-context --full               # Full detailed report
pmat analyze deep-context --include-pattern "*.rs" # Filter by file pattern
pmat analyze big-o                            # Big-O complexity analysis
pmat analyze makefile-lint                    # Makefile quality linting
pmat analyze proof-annotations                # Provability analysis

# Analysis commands
pmat analyze graph-metrics                    # Graph centrality metrics (PageRank, betweenness, closeness)
pmat analyze name-similarity "function_name"  # Fuzzy name matching with phonetic support
pmat analyze symbol-table                     # Symbol extraction with cross-references
pmat analyze duplicates --min-lines 10        # Code duplication detection
pmat quality-gate --fail-on-violation         # Comprehensive quality enforcement
pmat diagnose --verbose                       # Self-diagnostics and health checks

# WebAssembly Support
pmat analyze assemblyscript --wasm-complexity  # AssemblyScript analysis with WASM metrics
pmat analyze webassembly --include-binary      # WebAssembly binary and text format analysis

# Project scaffolding
pmat scaffold rust --templates makefile,readme,gitignore
pmat list                                      # Available templates

# Refactoring engine
pmat refactor interactive                      # Interactive refactoring
pmat refactor serve --config refactor.json     # Batch refactoring
pmat refactor status                          # Check refactor progress
pmat refactor resume                          # Resume from checkpoint
pmat refactor auto                            # AI-powered automatic refactoring
pmat refactor docs --dry-run                  # Clean up documentation

# Demo and visualization
pmat demo --format table                      # CLI demo
pmat demo --web --port 8080                   # Web interface
pmat demo --repo https://github.com/user/repo # Analyze GitHub repo

# Quality enforcement
pmat quality-gate --fail-on-violation         # CI/CD quality gate
pmat quality-gate --checks complexity,satd,security  # Specific checks
pmat quality-gate --format human              # Human-readable output
pmat enforce extreme                          # Enforce extreme quality standards

💫 See CLI usage in action

Context and code analysis:

Running demos/visualization:

MCP Integration

Using with Claude Code

# Add to Claude Code
claude mcp add pmat ~/.local/bin/pmat

💫 See Claude Code usage in action

Using the pmcp Rust SDK (NEW)

The MCP server can now be run using the pmcp Rust SDK for better type safety and async support:

// Run the MCP server with pmcp SDK
cargo run --example mcp_server_pmcp

// Or use as a library
use pmat::mcp_pmcp::{handlers::*, PmcpServer};
use pmcp::{Server, ServerBuilder};

let server = ServerBuilder::new("pmat-mcp", "1.0.0")
    .with_tool("analyze_complexity", "Analyze code complexity", 
        Box::new(AnalyzeComplexityTool))
    .with_tool("analyze_satd", "Detect technical debt",
        Box::new(AnalyzeSatdTool))
    // ... add more tools
    .build();

// Handle connections
server.handle_connection(stream).await?;

The pmcp SDK provides:

Type-safe tool definitions with proper async handling
Built-in JSON-RPC 2.0 protocol implementation
Automatic request/response serialization
Connection lifecycle management
Error handling and logging

Available MCP tools:

generate_template - Generate project files from templates
scaffold_project - Generate complete project structure
analyze_complexity - Code complexity metrics with tool composition
analyze_code_churn - Git history analysis
analyze_dag - Dependency graph generation
analyze_dead_code - Dead code detection
analyze_deep_context - Comprehensive analysis with tool composition
generate_context - Zero-config context generation
analyze_big_o - Big-O complexity analysis with confidence scores
analyze_makefile_lint - Lint Makefiles with 50+ quality rules
analyze_proof_annotations - Lightweight formal verification
analyze_graph_metrics - Graph centrality and PageRank analysis
refactor_interactive - Interactive refactoring with explanations

🔗 MCP Tool Composition (NEW)

AI agents can now chain analysis tools using the --files parameter:

# Step 1: Find complexity hotspots
pmat analyze complexity --top-files 5 --format json

# Step 2: Deep analyze those specific files (MCP composition)
pmat analyze comprehensive --files src/complex.rs,src/legacy.rs

# Step 3: Target refactoring on problematic files
pmat refactor auto --files src/complex.rs

MCP Agent Workflow Example:

// AI agent discovers hotspots
const hotspots = await callTool("pmat_analyze_complexity", {
  top_files: 5, 
  format: "json"
});

// Agent extracts file paths and performs deep analysis
const detailed = await callTool("pmat_analyze_comprehensive", {
  files: hotspots.files.map(f => f.path)
});

// Agent generates targeted refactoring plan
const refactor = await callTool("pmat_refactor_auto", {
  files: detailed.high_risk_files
});

HTTP API

# Start server
pmat serve --port 8080 --cors

# API endpoints
curl "http://localhost:8080/health"
curl "http://localhost:8080/api/v1/analyze/complexity?top_files=5"
curl "http://localhost:8080/api/v1/templates"

# POST analysis
curl -X POST "http://localhost:8080/api/v1/analyze/deep-context" \
  -H "Content-Type: application/json" \
  -d '{"project_path":"./","include":["ast","complexity","churn"]}'

🚀 CI/CD Integration

All analyze commands now support --fail-on-violation for seamless CI/CD integration:

GitHub Actions Example

name: Code Quality
on: [push, pull_request]

jobs:
  quality:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - uses: dtolnay/rust-toolchain@stable
      
      - name: Install pmat
        run: cargo install pmat
        
      - name: Check Complexity
        run: |
          pmat analyze complexity \
            --max-cyclomatic 15 \
            --max-cognitive 10 \
            --fail-on-violation
            
      - name: Check Technical Debt
        run: pmat analyze satd --strict --fail-on-violation
        
      - name: Check Dead Code
        run: |
          pmat analyze dead-code \
            --max-percentage 10.0 \
            --fail-on-violation
            
      - name: Run Quality Gate
        run: pmat quality-gate --fail-on-violation

Configurable Thresholds

Complexity: --max-cyclomatic (default: 20), --max-cognitive (default: 15)
Dead Code: --max-percentage (default: 15.0%)
SATD: Fails on ANY technical debt when using --fail-on-violation

Exit Codes

0: Success - no violations found or within thresholds
1: Failure - violations exceed configured thresholds

See examples/ci_integration.rs for more CI/CD patterns including GitLab CI, Jenkins, and pre-commit hooks.

Recent Updates

🐛 v0.29.6 - Critical Bug Fixes

Fixed Quality Gate Bug: Quality gate dead code detection now correctly analyzes code instead of always reporting violations
Fixed Include Patterns: --include patterns now properly work with test directories (e.g., --include "tests/**/*.rs")
Fixed Clippy Warning: Replaced deprecated map_or with is_some_and for cleaner code

🏆 v0.28.14 - Toyota Way Kaizen Success

Massive Complexity Reduction: Core handle_refactor_auto function complexity reduced from 136 → 21 (84% reduction)
Zero Quality Violations: Project now maintains 0 lint violations, 0 max complexity, 0 SATD comments
Toyota Way Implementation: Applied Kaizen (continuous improvement), Genchi Genbutsu (go and see), Jidoka (quality at source), and Poka-Yoke (error-proofing) principles
Code Size Optimization: Net reduction of 3,401 lines while improving functionality and maintainability
Comprehensive Testing: Added extensive property tests, doctests, and unit tests for all refactored components
Zero Compromise: No hacks, shortcuts, or technical debt introduced during refactoring

🚦 v0.28.9 - CI/CD Integration & Exit Codes

CI/CD Support: All analyze commands now support --fail-on-violation flag
Exit Codes: Commands exit with code 1 when violations exceed thresholds
Configurable Thresholds: Added --max-percentage for dead-code analysis
Examples: Added comprehensive CI/CD examples for GitHub Actions, GitLab CI, Jenkins
Documentation: Updated all documentation with CI/CD integration patterns

🔍 v0.28.3 - Enhanced Single-File Analysis

Single File Analysis: Added --file flag to pmat analyze comprehensive for analyzing individual files.
Bug Fix: Fixed "No such file or directory" error in single-file refactor mode by using dynamic executable path detection.
Test Improvements: Fixed stack overflow issues in CLI tests by using wildcard pattern matching.
Documentation: Updated CLI reference with new single-file analysis capabilities.

🚦 v0.28.2 - Quality Gate Improvements

Quality Gate Tests: Added comprehensive integration tests for CI/CD quality gates.
Public API: Made quality gate structs public for better testing support.
Doctests: Added doctests for quality gate and DAG generation functions.
Bug Fixes: Fixed mermaid test failures and unused import warnings.

🏆 v0.26.3 - Quality Uplift

SATD Elimination: Removed all TODO/FIXME/HACK comments from implementation.
Complexity Reduction: All functions now below a cyclomatic complexity of 20.
Extreme Linting: make lint passes with pedantic and nursery standards.
Single File Mode: Enhanced support for targeted quality improvements.

🧹 v0.26.1 - Documentation Cleanup (`pmat refactor docs`)

AI-assisted documentation cleanup to maintain Zero Tolerance Quality Standards.
Identifies and removes temporary files, outdated reports, and build artifacts.
Interactive mode for reviewing files before removal with automatic backups.

🔥 v0.26.0 - New Analysis Commands

Graph Metrics: pmat analyze graph-metrics for centrality analysis.
Name Similarity: pmat analyze name-similarity for fuzzy name matching.
Symbol Table: pmat analyze symbol-table for symbol extraction.
Code Duplication: pmat analyze duplicates for detecting duplicate code.

Toyota Way Quality Standards

This project exemplifies the Toyota Way philosophy through disciplined quality practices:

Kaizen (改善) - Continuous Improvement

84% Complexity Reduction: Achieved through systematic refactoring
Zero Quality Violations: Maintained through iterative improvement
Net -3,401 Lines: Simplified while enhancing functionality

Genchi Genbutsu (現地現物) - Go and See

Data-Driven Decisions: Used actual metrics to identify complexity hotspots
Root Cause Analysis: Fixed underlying architectural issues, not symptoms
Measurement-Based: Every improvement verified through quantitative analysis

Jidoka (自働化) - Quality at Source

ZERO SATD: No TODO, FIXME, HACK, or placeholder implementations
ZERO High Complexity: No function exceeds cyclomatic complexity of 20
ZERO Known Defects: All code must be fully functional
ZERO Incomplete Features: Only complete, tested features are merged

Poka-Yoke (ポカヨケ) - Error Prevention

Comprehensive Testing: Property tests, doctests, and unit tests prevent regressions
Automated Quality Gates: CI/CD integration prevents quality degradation
Type Safety: Rust's type system eliminates entire categories of errors

📊 Output Formats

JSON - Structured data for tools and APIs
Markdown - Human-readable reports
SARIF - Static analysis format for IDEs
Mermaid - Dependency graphs and diagrams

🎯 Use Cases

For AI Agents

Context Generation: Give AI perfect project understanding
Code Analysis: Deterministic metrics and facts
Template Generation: Scaffolding with best practices

For Developers

Code Reviews: Automated complexity and quality analysis
Technical Debt: SATD detection and prioritization
Onboarding: Quick project understanding
CI/CD: Integrate quality gates and analysis

For Teams

Documentation: Auto-generated project overviews
Quality Gates: Automated quality scoring
Dependency Analysis: Visual dependency graphs
Project Health: Comprehensive health metrics

🚦 CI/CD Quality Gates

GitHub Actions Integration

# .github/workflows/quality.yml
- name: Run Quality Gate
  run: |
    pmat quality-gate \
      --checks complexity,satd,security,dead-code \
      --max-complexity-p99 20 \
      --fail-on-violation

Available Quality Checks

complexity - Cyclomatic complexity thresholds
satd - Self-admitted technical debt (TODO/FIXME/HACK)
security - Hardcoded passwords and API keys
dead-code - Unused functions and variables
entropy - Code diversity metrics
duplicates - Code duplication detection
coverage - Test coverage thresholds
sections - Required documentation sections
provability - Formal verification readiness

📚 Documentation

Explore our comprehensive documentation to get the most out of pmat.

Getting Started

Architecture: Understand the system design and principles.
CLI Reference: View the full command-line interface guide.
API Documentation: Browse the complete Rust API documentation on docs.rs.

Usage Guides

Feature Overview: Discover all available features.
MCP Integration: Learn how to integrate pmat with AI agents.
CI/CD Integration: Set up quality gates in your CI/CD pipeline.

Development

Contributing Guide: Read our guidelines for contributing to the project.
Release Process: Follow our step-by-step release workflow.

🛠️ System Operations

Memory Management

For systems with low swap space, we provide a configuration tool:

make config-swap      # Configure 8GB swap (requires sudo)
make clear-swap       # Clear swap memory between heavy operations

🧪 Testing

The project uses a distributed test architecture for fast feedback:

# Run specific test suites
make test-unit        # <10s - Core logic tests
make test-services    # <30s - Service integration
make test-protocols   # <45s - Protocol validation
make test-e2e         # <120s - Full system tests
make test-performance # Performance regression

# Run all tests in parallel
make test-all

# Coverage analysis
make coverage-stratified

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

Quick Start for Contributors

# Clone and setup
git clone https://github.com/paiml/paiml-mcp-agent-toolkit
cd paiml-mcp-agent-toolkit

# Install dependencies
make install-deps

# Run tests
make test-fast      # Quick validation
make test-all       # Complete test suite

# Check code quality
make lint           # Run extreme quality lints
make coverage       # Generate coverage report

Development Workflow

Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Make your changes following our Zero Tolerance Quality Standards

Run quality checks before committing:

make lint  # Check code quality
make test  # Run all tests (fast, doctests, property tests, examples)

Submit a pull request with a clear description of changes

Note: The make test command runs comprehensive testing including:

⚡ Fast unit and integration tests
📚 Documentation tests (doctests)
🎲 Property-based tests
📘 All cargo examples

See CONTRIBUTING.md for detailed guidelines.

📄 License

Licensed under either of:

Apache License, Version 2.0 (LICENSE-APACHE)
MIT license (LICENSE-MIT)

at your option.

Built with ❤️ by Pragmatic AI Labs

PAIML MCP Agent Toolkit