footprintjsMCP Server30/100 via “rule engine integration and decision tree visualization”
Explainable backend flows — automatic causal traces, decision evidence, and MCP tool generation for AI agents
Unique: Automatically instruments rule evaluation to capture which rules matched and in what order, then generates interactive visualizations that show the actual execution path rather than just the static rule structure, enabling business users to understand decisions without code knowledge
vs others: More actionable than static rule documentation because it shows the actual execution path taken for specific inputs, and more comprehensive than simple rule logging because it includes conflict detection and coverage analysis