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PhpCodeArcheology

PhpCodeArcheology

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PhpCodeArcheology

Packagist Version PHP Version License PhpCodeArcheology MCP server

PhpCodeArcheology is a PHP static analysis tool that measures code quality through 60+ metrics including cyclomatic complexity, maintainability index, coupling, and cohesion. It generates comprehensive reports for files, classes, methods, and functions — detecting code smells, identifying hotspots via git churn analysis, and tracking quality trends over time.

Unlike PHPStan or Psalm (which focus on type safety and bug detection), PhpCodeArcheology focuses on architecture and maintainability — giving you the insights you need to understand and improve your codebase structure. Think of it as an alternative to PHPMetrics with deeper git integration, baseline management, and AI-ready output.

PhpCodeArcheology Dashboard

AI Integration (MCP Server)

PhpCodeArcheology is the first PHP static analysis tool with native MCP (Model Context Protocol) support — meaning AI assistants like Claude can query your codebase analysis results directly, without reading files or parsing JSON manually.

Quick Start with Claude Code

The setup depends on how you installed PhpCodeArcheology:

Global installation (composer global require php-code-archeology/php-code-archeology):

claude mcp add phpcodearcheology -- phpcodearcheology mcp

Project dependency (composer require --dev php-code-archeology/php-code-archeology):

claude mcp add phpcodearcheology -- vendor/bin/phpcodearcheology mcp

Or drop a .mcp.json into your project root for team sharing:

{
  "mcpServers": {
    "phpcodearcheology": {
      "command": "vendor/bin/phpcodearcheology",
      "args": ["mcp"]
    }
  }
}

Once connected, Claude can answer questions like "Which classes have the highest technical debt?", "Show me all God Classes", or "What are the top refactoring priorities in this project?" — using live analysis data.

Available MCP Tools

Tool

Description

get_health_score

Overall code health score, grade, and project statistics

get_problems

Code quality problems, filterable by severity and type

get_metrics

Detailed metrics for a specific class, file, or function

get_hotspots

Git hotspots ranked by churn × complexity

get_refactoring_priorities

Ranked refactoring candidates with recommendations

get_dependencies

Class dependency analysis (incoming/outgoing)

get_class_list

All classes with key metrics, sortable and filterable

get_graph

Knowledge graph as JSON (nodes, edges, cycles)

get_impact_analysis

Impact analysis: what breaks if you change a method? Shows callers and call chains

get_test_coverage

Test coverage summary — tested/untested classes, coverage gaps, test mapping

search_code

Search entities by name with metric overview

Features

  • 60+ code quality metrics per file, class, and function — cyclomatic complexity, cognitive complexity, maintainability index, LCOM, Halstead metrics, coupling, instability, and more

  • Problem detection with 14 built-in rules — God Class, too complex, dead code, security smells, SOLID violations, deep inheritance, low type coverage, untested complex code

  • Test analysis — auto-detects PHPUnit/Pest/Codeception, maps test files to production classes, integrates Clover XML for line-level coverage, highlights untested hotspots

  • Git integration — churn analysis, hotspot detection (high churn + high complexity), author tracking

  • Multiple report formats — interactive HTML, Markdown, JSON, SARIF (GitHub Code Scanning), AI summary, Knowledge Graph (JSON)

  • Health Score — single 0-100 score with A-F grading for your entire project

  • Technical Debt Score — weighted problem score normalised per 100 logical lines of code

  • History tracking — trend charts across multiple analysis runs

  • Baseline management — track only new problems, ignore existing ones (ideal for legacy projects)

  • CI/CD ready — configurable exit codes, SARIF for GitHub Code Scanning, JSON for custom tooling

  • Quick mode — fast terminal-only output without report generation

  • CLAUDE.md generation — auto-generated project overview for AI coding assistants

Prerequisites

  • PHP 8.2 or higher (works on 8.2, 8.3, 8.4, 8.5)

  • Composer

Installation

composer require --dev php-code-archeology/php-code-archeology

Global Installation

composer global require php-code-archeology/php-code-archeology

Make sure ~/.composer/vendor/bin (or ~/.config/composer/vendor/bin) is in your $PATH. Then run from any directory:

phpcodearcheology /path/to/your/project

Docker

docker build -t phpcodearcheology https://github.com/PhpCodeArcheology/PhpCodeArcheology.git

Run against a local project:

docker run --rm -v "$(pwd)":/project -v "$(pwd)/report":/output phpcodearcheology /project

This mounts your project into the container and writes the HTML report to ./report/.

Quick Start

Run in your project root:

./vendor/bin/phpcodearcheology

No config file needed — the tool works out of the box. It scans your src directory and creates an HTML report in tmp/report. Open tmp/report/index.html in your browser.

Tip: Add tmp/report to your .gitignore to keep generated reports out of version control.

Using the Composer Plugin

PhpCodeArcheology registers itself as a Composer plugin, so you can run the analysis directly via Composer:

composer codearch:analyze

When no path is given and no config file exists, it automatically detects your PSR-4 source directories from composer.json. All CLI options are supported:

composer codearch:analyze -- --quick
composer codearch:analyze -- --report-type=json --coverage-file=clover.xml
composer codearch:analyze -- src/ lib/

To create a config file interactively:

./vendor/bin/phpcodearcheology init

Memory and Performance

The directories vendor/, node_modules/, and .git/ are excluded automatically — you don't need to configure this. If you point the tool at your project root, only your own code is analysed.

For large codebases (50k+ files), analysis may require more memory than the default 1G. The tool respects your php.ini memory_limit — if you've set it to -1 (unlimited), it stays unlimited. To adjust the limit per project, add memoryLimit to your config file:

# php-codearch-config.yaml
memoryLimit: "2G"    # or "-1" for unlimited

Test Analysis

PhpCodeArcheology automatically detects your test infrastructure from composer.json (PHPUnit, Pest, or Codeception) and maps test files to production classes using PSR-4 namespaces, naming conventions, and directory structure.

What you get out of the box:

  • Per-class hasTest flag and test file count in the HTML/Markdown/JSON reports

  • UntestedComplexCode warnings for classes with cyclomatic complexity ≥ 8 and no tests (only when test infrastructure is detected)

  • untested as a refactoring priority driver

  • A Tests page in the HTML and Markdown reports with a coverage gaps table and dashboard tiles

Important note on Pest: Pest's function-based tests (it(...), test(...)) contain no class declaration and cannot be mapped to production classes by name alone. To get accurate coverage for Pest projects, generate a Clover XML report — this tracks actual line execution regardless of test style.

With Clover XML coverage data (optional, recommended for Pest), you get line-level coverage per class:

# Generate coverage first (requires Xdebug or PCOV PHP extension)
XDEBUG_MODE=coverage vendor/bin/pest --coverage-clover clover.xml
# or: XDEBUG_MODE=coverage vendor/bin/phpunit --coverage-clover clover.xml

# PhpCodeArcheology auto-detects clover.xml in common locations (project root, build/logs/, etc.)
./vendor/bin/phpcodearcheology src/

# Or specify explicitly:
./vendor/bin/phpcodearcheology --coverage-file clover.xml src/

Coverage data is factored into the Health Score as a 10th factor (10% weight). The get_test_coverage MCP tool exposes all coverage data to AI assistants.

CLI Options

./vendor/bin/phpcodearcheology [options] [path...]

Option

Description

--report-type=TYPE

Report format: html (default), markdown, json, sarif, ai-summary, graph. Comma-separated for multiple: html,json

--report-dir=DIR

Output directory (default: tmp/report)

--quick

Fast analysis with terminal output only, no report generation

--no-color

Disable coloured terminal output (also respects NO_COLOR env)

--fail-on=LEVEL

Exit 1 on error or warning (for CI pipelines)

--generate-claude-md

Generate a CLAUDE.md project overview

--git-root=DIR

Git repository root (default: current directory)

--extensions=EXT

File extensions to analyse (comma-separated, default: php)

--exclude=DIR

Directories to exclude (comma-separated)

--coverage-file=FILE

Clover XML coverage file from PHPUnit/Pest for line-level coverage data

--version

Show version

Subcommands

init — Create Config File

./vendor/bin/phpcodearcheology init

Interactively creates a php-codearch-config.yaml with sensible defaults. Detects common source directories (src, app, lib) automatically.

compare — Compare Two Reports

./vendor/bin/phpcodearcheology compare report-before.json report-after.json

Shows a delta view of metrics, problem counts, and lists new/resolved problems. Useful for answering: "Did my refactoring actually help?"

baseline — Track New Problems Only

./vendor/bin/phpcodearcheology baseline create src
./vendor/bin/phpcodearcheology baseline check src

create saves the current problem set as a baseline. check runs a fresh analysis and reports only problems that are new compared to the baseline. Returns exit code 1 if new errors are found — ideal for CI pipelines on legacy projects.

Configuration

Create a php-codearch-config.yaml in your project root (or use init):

include:
  - "src"

exclude:
  - "vendor"

extensions:
  - "php"

packageSize: 2

reportDir: "tmp/report"
reportType: "html"

git:
  enable: true
  since: "6 months ago"
  root: "."  # Git repository root (useful for monorepos or subdirectory analysis)

graph:
  methodCalls: true  # Track cross-class method calls in the knowledge graph (default: true)

php:
  version: "8.2"       # Target PHP version for parsing (default: host PHP version)
  shortOpenTags: false  # Treat <? as PHP open tag (default: false)

framework:
  detect: true                    # Auto-detect Symfony/Laravel/Doctrine from composer.json (default: true)
  adjustments:
    doctrineCycles: true          # Downgrade Entity↔Repository cycles to info (default: true)
    entityCycles: true            # Downgrade Entity↔Entity ORM cycles to info (default: true)
    controllerThresholds: true    # Raise dependency thresholds for controllers (default: true)

qualityGate:
  maxErrors: 0
  maxWarnings: 10

thresholds:
  tooLong:
    file: 400
    class: 300
    function: 40
    method: 30
  tooComplex:
    cc: 10
    ccLargeCode: 20
    difficulty: 20
    cognitiveComplexity: 15
    avgMethodCc: 10
  tooManyParameters:
    warning: 4
    error: 7
  tooDependent:
    function: 10
    class: 20
  lowTypeCoverage:
    warning: 60
    error: 40
  deepInheritance:
    warning: 4
    error: 6
  tooMuchHtml:
    filePercent: 25
    classPercent: 10
    fileOutput: 10
    classOutput: 4
  hotspot:
    minChurn: 10
    minCc: 15
  lcomExclude:
    patterns:        # Class name patterns to skip LCOM warnings (fnmatch)
      - "*Exception"
      - "*Error"
    interfaces:      # Implemented interfaces that justify low cohesion
      - "EventSubscriberInterface"
      - "EventListenerInterface"

Note: Enums, interfaces, traits, and classes with 0-1 methods are always excluded from LCOM warnings regardless of configuration.

All threshold values shown above are the defaults. You only need to specify values you want to override.

Report Types

Type

Subdirectory

Output

Use Case

html

html/

Interactive HTML report with charts

Browser-based review

markdown

markdown/

Markdown files

Text-based review, Git-friendly

json

json/

report.json

Machine processing, custom tooling

sarif

sarif/

report.sarif.json

GitHub Code Scanning, VS Code SARIF Viewer

ai-summary

ai-summary/

ai-summary.md

Token-efficient summary for LLM consumption

graph

graph/

graph.json

Knowledge Graph (nodes + edges) for AI tools and visualisations

Since v1.6.0, each report type writes into its own subdirectory. history.jsonl remains in the report root.

tmp/report/
├── html/
│   └── index.html
├── json/
│   └── report.json
├── sarif/
│   └── report.sarif.json
├── markdown/
│   └── ...
├── ai-summary/
│   └── ai-summary.md
├── graph/
│   └── graph.json
└── history.jsonl

Generate multiple report types in one run:

./vendor/bin/phpcodearcheology --report-type=html,json

Upgrading from v1.5.x? Old report files in the report root (e.g. index.html, report.json) are no longer overwritten. They can be safely deleted.

Knowledge Graph Export

The graph report type exports your codebase structure as a machine-readable Knowledge Graph — designed for AI tools, graph databases, and custom visualisations.

./vendor/bin/phpcodearcheology --report-type=graph --report-dir=output src/
# Writes: output/graph/graph.json

The JSON output contains four top-level arrays:

nodes — five types of nodes, each with an id, type, name, metrics, and flags:

Node type

Metrics

class

cc, lcom, mi, instability, afferentCoupling, efferentCoupling, gitChurnCount, gitCodeAgeDays

method

cc, cognitiveComplexity, params

function

cc, cognitiveComplexity, params

package

abstractness, instability, distanceFromMainline

author

commitCount, filesChanged

edges — relationships between nodes:

Edge type

Meaning

declares

Class → Method

extends

Class → Parent class

implements

Class → Interface

uses_trait

Class → Trait

depends_on

Class → Class (via new / static call)

calls

Method → Method (cross-class calls via new / static call, weight = call-site count)

belongs_to

Class → Package

authored_by

Class → Author

cycle_member

Class ↔ Class (dependency cycle, bidirectional)

clusters — classes grouped by package.

cycles — detected dependency cycles with the involved class node IDs.

{
  "version": "1.0",
  "generatedAt": "2026-03-24T12:00:00+00:00",
  "nodes": [
    { "id": "class:x1a2b3c4", "type": "class", "name": "App\\UserService",
      "path": "/src/UserService.php",
      "metrics": { "cc": 12, "lcom": 3, "mi": 65.2, "instability": 0.8,
                   "afferentCoupling": 5, "efferentCoupling": 20,
                   "gitChurnCount": 15, "gitCodeAgeDays": 42 },
      "flags": { "interface": false, "trait": false, "abstract": false,
                 "final": false, "enum": false },
      "problems": [] }
  ],
  "edges": [
    { "source": "class:x1a2b3c4", "target": "class:x9c0d1e2f",
      "type": "depends_on", "weight": 1 }
  ],
  "clusters": [
    { "id": "package:App\\Services", "name": "App\\Services",
      "nodeIds": ["class:x1a2b3c4"] }
  ],
  "cycles": [
    { "nodes": ["class:xabc123", "class:xdef456"], "length": 2 }
  ]
}

Key Metrics

Metric

Description

Cyclomatic Complexity (CC)

Number of independent paths through code. Below 5 is good, above 10 needs attention.

Cognitive Complexity

How difficult code is to understand (considers nesting depth).

Maintainability Index (MI)

Composite score from CC, Halstead volume, and LOC. Above 85 is good, below 65 is concerning.

LCOM

Lack of Cohesion of Methods — how well a class's methods relate to each other. Lower is better.

Halstead Metrics

Difficulty, effort, volume, and vocabulary based on operators/operands.

Type Coverage

Percentage of parameters and return values with type declarations.

Instability

Ratio of efferent to total coupling (0 = stable, 1 = unstable).

Technical Debt Score

Weighted problem points per 100 logical lines of code.

Health Score

Overall project quality grade from A (excellent) to F (critical).

For detailed descriptions, formulas, thresholds, and interpretation guidelines, see the Metric Reference.

The HTML report also includes a full Metric Glossary with descriptions, thresholds, and severity levels.

Development

The HTML report templates use Tailwind CSS. The compiled output.css is committed to the repository, so you do not need Node.js to use or contribute to this project.

If you modify HTML templates or CSS, rebuild with:

npm install
npm run build:css

For live rebuilding during development:

npm run watch:css

A Note on Metric Accuracy (v2.7.0)

I use PhpCodeArcheology extensively on my own projects to track code quality over time. While doing so, I noticed that some metric values didn't quite add up — method-level Halstead difficulty seemed too high, certain classes were flagged as God Classes when they shouldn't have been, and error counts felt inflated.

After a thorough review, I found and fixed several calculation bugs that had been present since earlier versions. The most impactful was a Halstead operand tracking bug at the method level, along with double-counting in complexity predictions, false positives in God Class detection, and a few other issues.

I sincerely apologize for the inaccuracy. A code analysis tool must be trustworthy above all else, and these bugs undermined that. Version 2.7.0 corrects all known calculation issues, and I've added hand-calculated test fixtures to ensure the formulas stay correct going forward.

What this means for you: If you're upgrading from an earlier version, your analysis results will change — most notably, error counts will decrease significantly and Health Scores will improve. The tool will show a one-time notice on first run. See docs/metrics-formulas.md for a detailed breakdown of every change and its expected impact.

Understanding the Health Score

The Health Score (0–100) is a guideline for tracking trends, not an absolute judgment of code quality. Some things to keep in mind:

  • Complex domains produce complex code. A financial calculation engine, a protocol parser, or a compiler will naturally have higher Halstead Difficulty and Cyclomatic Complexity than a REST API. That's expected, not a defect.

  • Scores are most useful over time. A project that moves from 65 to 72 over six months is improving — even if it never reaches 90.

  • Focus on outliers, not the average. The most actionable insight is which classes deviate significantly from your project's baseline. Those are your refactoring candidates.

  • Don't compare across projects. A score of 80 in a Symfony application is not the same as 80 in a CLI tool. Different architectures and domains have different natural complexity floors.

The score is weighted across 10 factors (Maintainability Index, Problem Density, Complexity, Coupling, Code Structure, HTML Ratio, Encapsulation, Dependencies, Abstractness, and Test Coverage). See docs/metrics-formulas.md for the exact formulas and weights.

Contributing

Contributions are welcome! Check the open issues for bugs and feature requests, or see the Roadmap for planned features. For larger changes, open an issue first to discuss the approach.

Author

Marcus Kober — GitHub

License

MIT

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