Webber-Lubenham / mcp-ai-universe
Code health
Webber-Lubenham/mcp-ai-universe scores 9.6 out of 10 on defect risk, which Repowise rates Excellent. Maintainability scores 9.4 out of 10. Static performance risk scores 10.0 out of 10. The three are scored separately and never blended into a single number.
Full health report- Files
- 67
- Symbols
- 141
- Modules
- 16
- Doc pages
- 60
- Dead exports
- 68
Read more about Webber-Lubenham/mcp-ai-universe
- OverviewFiles, symbols, languages, packages, git intelligence
- ArchitectureDependency graph, layered architecture, symbol index, and third-party dependencies
- Code healthPer-file health scores, hotspots, test coverage, dead code, and refactoring targets
- AI explanationsProModule-by-module documentation generated from source
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[](https://repowise.dev/repo/Webber-Lubenham/mcp-ai-universe)Code health badge
Average health across every file, straight from the latest index.
[](https://repowise.dev/repo/Webber-Lubenham/mcp-ai-universe)How Webber-Lubenham/mcp-ai-universe works
This page is an auto-generated, always-fresh map of the Webber-Lubenham/mcp-ai-universe repository, written primarily in typescript. Repowise indexes the source, parses every symbol, computes a dependency graph, scores per-file code health from complexity, duplication, test coverage and churn, mines git history for hotspots and ownership, and lifts the resulting architectural decisions into a wiki you can read or query through MCP.
The codebase has 67 source files, 141 symbols, and 4 languages, organised into 16 modules, led by typescript, json, javascript. Static analysis leaves 43 open findings across the three health dimensions.
Use the links above to open the interactive dashboards, or connect this repo to your editor via the Repowise MCP server for grounded answers inside Claude, Cursor, or VS Code.