🏗️ ArchLens - Advanced Architecture Analysis Tool

🔍 Intelligent code architecture analysis with AI-powered insights

Discover code smells, architectural antipatterns, and technical debt in your projects

📖 Documentation • 🚀 Quick Start • 🤖 AI Integration

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🌟 Features

🔍 Deep Code Analysis

• Code Smells Detection: Long methods, magic numbers, code duplication
• SOLID Principles: Violations of single responsibility, open/closed principles
• Architectural Antipatterns: God Objects, tight coupling, circular dependencies
• Quality Metrics: Cyclomatic complexity, cognitive complexity, maintainability index

🏗️ Architecture Insights

• Project Structure: Hierarchical analysis with layer detection
• Dependency Mapping: Import/export relationships and circular dependencies
• Technical Debt: Quantified debt assessment with refactoring recommendations
• Risk Assessment: Automated architectural risk evaluation

🤖 AI-Ready Output

• MCP Server (Rust, STDIO): Official STDIO JSON-RPC with JSON Schema publishing (no HTTP)
• Structured Reports: JSON/Markdown exports optimized for AI consumption
• Interactive Diagrams: Mermaid diagrams for visual architecture representation
• Context-Rich: Detailed explanations suitable for AI-assisted refactoring

🛠️ Developer Experience

• Multi-Language: Rust, TypeScript, JavaScript, Python, Java, Go, C/C++
• Cross-Platform: Windows, macOS, Linux support
• CLI & Library: Command-line interface and Rust library API
• No Admin Rights: Works without elevated permissions

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🚀 Quick Start

📦 Installation

Build from Source

# Clone repository
git clone https://github.com/yourusername/archlens.git
cd archlens

# Build release binaries
cargo build --release

# Binaries will be available at ./target/release/archlens and ./target/release/archlens-mcp

🔍 Basic Usage (CLI)

📊 Project Analysis

# Analyze current directory
./target/release/archlens analyze .

# Analyze specific project
./target/release/archlens analyze /path/to/project

📁 Project Structure

./target/release/archlens structure . --show-metrics

🤖 AI-Ready Export

# Export comprehensive analysis for AI (summary detail level by default)
./target/release/archlens export . ai_compact --output analysis.md

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🤖 AI Integration

🔌 MCP Server (Model Context Protocol, Rust, STDIO)

The ArchLens MCP server provides a clean STDIO JSON‑RPC interface (no HTTP). It exposes:

• Methods: tools/list, tools/call, resources/list, resources/read, prompts/list, prompts/get
• Tool names returned via tools/list use underscore format (e.g., export_ai_summary_json), while calls accept both underscore and dotted aliases (e.g., export.ai_summary_json).

🛠️ Run with MCP Inspector

# Build the server
cargo build --release --bin archlens-mcp

# Start MCP Inspector against the server (stdio)
npx @modelcontextprotocol/inspector -- ./target/release/archlens-mcp
# Open the printed Inspector URL to interactively test tools/resources/prompts

🧪 STDIO Examples

{"jsonrpc":"2.0","id":1,"method":"tools/list"}
{"jsonrpc":"2.0","id":2,"method":"tools/call","params":{"name":"export_ai_summary_json","arguments":{"project_path":".","top_n":5}}}
{"jsonrpc":"2.0","id":3,"method":"tools/call","params":{"name":"ai_recommend","arguments":{"project_path":".","json":{}}}}

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🛠️ Development

🔧 Building

# Development build
cargo build

# Release build with optimizations
cargo build --release

# Run tests
cargo test

# Run with logging
RUST_LOG=debug cargo run --bin archlens -- analyze .

🧪 Testing

# Run all tests
cargo test

# With output
cargo test -- --nocapture

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📄 License

This project is licensed under the MIT License - see the LICENSE file for details.