pyscn-mcp

Python Code Quality Analysis with pyscn MCP

Use the pyscn MCP tools for Python code quality analysis.

Available Tools

Tool	Purpose
get_health_score	Overall code health score (0-100) with grade
analyze_code	Comprehensive analysis (complexity, dead code, clones, coupling, deps)
check_complexity	Cyclomatic complexity of functions
detect_clones	Duplicate code detection
find_dead_code	Unreachable code detection
check_coupling	Class coupling (CBO) metrics

Tool Selection Guide

User Request	Tool
"How healthy is this code?"	get_health_score
"Analyze code quality"	analyze_code
"Find complex functions"	check_complexity
"Find duplicate code"	detect_clones
"Find dead code"	find_dead_code
"Check class coupling"	check_coupling

Common Parameters

• path (required): Path to Python file or directory
• recursive (analyze_code): Recursively analyze directories (default: true)
• analyses (analyze_code): Array of analyses to run - complexity, dead_code, clone, cbo, deps

Examples

Quick Health Check

Use get_health_score for a quick overview:

• Returns score 0-100 with letter grade (A-F)
• Category breakdowns for maintainability, reliability, etc.

Detailed Analysis

Use analyze_code with specific analyses:

• analyses: ["complexity"] - Only complexity
• analyses: ["clone"] - Only duplicates
• analyses: ["dead_code"] - Only dead code
• analyses: ["complexity", "dead_code"] - Multiple

Complexity Thresholds

Use check_complexity with:

• min_complexity: Minimum to report (default: 1)
• max_complexity: Maximum allowed (default: 0 = no limit)

Clone Detection

Use detect_clones with:

• similarity_threshold: 0.0-1.0 (default: 0.8)
• min_lines: Minimum lines to consider (default: 5)

Always explain results and suggest improvements based on findings.