ArchGuard backend

ArchGuard is an architecture governance tool that can analysis architecture in container, component, code level, database, create architecture fitness functions, and test for architecture rules.

Chinese: ArchGuard 是一个针对于微服务（分布式场景）下的架构工作台/治理工具。它可以帮助架构师、开发人员进行架构自助，自定义架构的洞察、 分析系统间的远程服务依赖情况、数据库依赖、API 依赖等。并根据一些架构治理模型，对现有系统提出改进建议。

• Document: https://archguard.org/
• Roadmap: Roadmap
• Contribute: Contribute to Archguard
• SubProjects:
  • ArchGuard Frontend
  • Chapi source code analysis
  • ArchGuard Co-mate an AI-powered architecture copilot, design and governance tools.
• Architecture:

You can use:

• ArchGuard Library in Maven Central to integrate with your backend.
• ArchGuard Scanner CLI to scan your codebase, upload to your backend or ArchGuard backend.
• ArchGuard Gradle Plugin to scan your codebase in CI/CD.
• ArchGuard Web is the backend of ArchGuard, it provides a RESTful API for frontend.

特性（Features）：

• 设计态
  • 架构设计、分析与治理 DSL
  • Feakin: https://github.com/feakin/fklang
• 开发态
  • 架构扫描
    • 扫描配置
    • 插件化规则定制
    • 规则化治理：Code Smell, Test Code Smell, SQL Smell, API Smell, Documentation Smell, etc.
  • 架构可视化
    • 基于 C4 模型的可视化分析
      • 上下文：API 服务地图（API 生产者支持语言：Java、Kotlin、C#，API 消费者支持语言：TypeScript/JavaScript、Kotlin、Java 等）
      • 容器分析。数据库地图（支持 MyBatis、JDBI、JPA）
      • 组件分析
      • 代码分析：支持级别模块、包、类、方法四个级别。
    • 高级分析 + 可视化
      • 系统不稳定性模块分析。
      • 容器间：精准测试/变化分析
  • 架构指标（单体DONE，分布式DOING）
    • 体量维度：过大的组件
    • 耦合维度：枢纽组件，过深调用，循环依赖
    • 内聚维度：霰弹式修改
    • 冗余维度：冗余元素，过度泛化
    • 质量维度：测试保护
  • 代码分析
    • CLOCO：代码复杂度 #79
    • SCA 分析
    • OpenAPI 分析
    • Architecture analysis
• 运行态
  • APM（TODO）
• 架构工作台

Features：

• Design State
  • Architecture Design, Analysis and Governance DSL
  • Feakin: https://github.com/feakin/fklang
• Development state
  • Schema scan
    • Scan configuration
    • Plug-in rule customization
    • Rule-based governance: Code Smell, Test Code Smell, SQL Smell, API Smell, Documentation Smell, etc.
  • Architecture visualization
    • Visual analysis based on C4 model
      • Context: API service map (API producer supported languages: Java, Kotlin, C#, API consumer supported languages: TypeScript/JavaScript, Kotlin, Java, etc.)
      • Container analysis. Database map (support MyBatis, JDBI, JPA)
      • Component analysis
      • Code analysis: supports four levels of modules, packages, classes, and methods.
    • Advanced Analysis + Visualization
      • System instability module analysis.
      • Between containers: precise testing/variation analysis
  • Architecture metrics (single DONE, distributed DOING)
    • Volume dimension: oversize components
    • Coupling dimension: hub components, too deep calls, circular dependencies
    • Cohesive Dimension: Shotgun Modification
    • Redundant dimensions: redundant elements, overgeneralization
    • Quality dimension: test protection
    • Continuous Integration
  • External analysis
    • CLOCO: Code Complexity #79
    • SCA analysis
    • OpenAPI analysis
    • Architecture analysis
• Running state
  • APM (TODO)
• Architecture Workbench

Screenshots:

Languages parse by Chapi

Features/Languages	Java	Python	Go	Kotlin	TypeScript	C	C#	Scala	C++
http api decl	✅	🆕	🆕	✅	✅	🆕	✅	🆕	🆕
syntax parse	✅	✅	✅	✅	✅	✅	✅	✅	🆕
function call	✅	🆕	✅	✅	✅
arch/package	✅			✅	✅	🆕	✅	✅
real world validate	✅				✅

Custom Backend

case example:

• https://github.com/unit-mesh/co-unit by Rust language

use Scanner CLI you can customize your backend. For more detail, see in: ArchGuardHttpClient

HTTP examples:

POST http://127.0.0.1:8765/scanner/:systemId/reporting/class-items

POST http://127.0.0.1:8765/scanner/:systemId/reporting/openapi

POST http://127.0.0.1:8765/scanner/:systemId/reporting/container-services

POST http://127.0.0.1:8765/scanner/:systemId/reporting/datamap-relations

...

MCP Server (Model Context Protocol)

🚀 New Feature Proposal: Expose ArchGuard's architecture linter as an MCP server for AI-assisted development!

The MCP server would enable AI assistants (Claude, ChatGPT, etc.) and development tools to leverage ArchGuard's linting capabilities through a lightweight, standardized interface.

Key Benefits:

• ⚡ Lightweight: <100MB memory, <2s startup (vs. full server)
• 🤖 AI Integration: Works with Claude, ChatGPT, GitHub Copilot
• 🔌 Standard Protocol: Compatible with any MCP-enabled tool
• 🎯 Stateless: Quick analysis without database overhead

Documentation:

• Detailed Proposal - Full specification and architecture
• GitHub Issue Template - Ready to submit feature request
• Implementation Guide - Step-by-step development guide

This would complement the existing server and CLI, adding a modern AI-friendly interface for architectural governance.

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Thanks

JetBrains support:

License

This code is distributed under the MIT license. See LICENSE in this directory.