$ loading_
Analyze codebase health and detect dead code, dependency, and architecture issues.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "CodeHealth MCP" yet — see the docs or source repo.
Analyze this repository's health and identify dead code, circular dependencies, high coupling, and architectural drift. Rank findings by severity and suggest fixes.
A prioritized issue list with risk explanations, impact scope, and recommended fixes.
Scan the current project's module dependency graph, list all circular dependency chains, identify affected files, and suggest refactoring options.
A list of circular dependencies, affected file paths, and actionable decoupling recommendations.
Evaluate whether the current code structure shows architectural drift, identify modules that violate expected boundaries, and recommend how to restore clearer layering.
An architectural drift analysis describing boundary violations and follow-up remediation guidance.
Index codebases into Neo4j for analysis, dependency mapping, and impact assessment.
Analyze codebases with metrics, thresholds, and quality checks for faster reviews.
Gives AI coding agents a structural map of your repository fast.
Gives AI coding agents repository intelligence, dependency analysis, and impact insights.
Analyze codebases, generate project docs, and map knowledge for better AI context.
Search, analyze, navigate, and scan multilingual codebases without API keys.