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pyscn

Official

by ludo-technologies · Go

Python code analysis for AI agents: complexity, dead code, clones, coupling, and a health score.

io.github.ludo-technologies/pyscn — Model Context Protocol (MCP) Server

This MCP server performs Python code analysis for AI agents. It focuses on metrics such as complexity, dead code detection, code clones, coupling, and produces a health score. The server’s purpose is described as providing these analysis results for downstream agent workflows.

🛠️ Key Features

  • Python code analysis for AI agents
  • Complexity metrics
  • Dead code detection
  • Code clone detection
  • Coupling measurement
  • Health score

🚀 Use Cases

  • Assessing Python code complexity for AI-driven evaluation
  • Identifying dead code in Python projects
  • Detecting code clones as part of refactoring guidance
  • Measuring coupling to understand maintainability
  • Generating a health score for codebase condition tracking

⚡ Developer Benefits

  • Centralized analysis for AI agents
  • Actionable software quality signals: complexity, dead code, clones, coupling, health score

⚠️ Limitations

  • Limited to the analysis areas explicitly described: complexity, dead code, clones, coupling, and health scoring

Topics

architecture-analysisclone-detectioncode-complexitydependency-analysispythonstatic-analysisdead-code-detection