70
/100
B
◉ Complete 5⁄4
MCP4DRL
Exposes a trained Deep Q-Network agent for business process resource allocation, enabling natural language interaction with reinforcement learning models. It provides tools for simulation control, Q-value analysis, and action explainability to make complex decision-making transparent.
Glama
Complete visibility
— 5/4 applicable dimensions scored
✓ Schema Quality
✓ Protocol
— Reliability
✓ Docs & Maintenance
✓ Security Hygiene
✓ Schema Interpretability
Schema Quality
78
42% weight
Protocol Compliance
N/A
Local server
Reliability
N/A
Local server
Docs & Maintenance
25
25% weight
Security Hygiene
92
33% weight
Schema Interpretability
100
15% weight
Score History
Category Trends
Static Analysis
| Metric | Score | Rating |
|---|---|---|
| Schema Completeness | 70 | Good |
| Description Quality | 90 | Good |
| Documentation Coverage | 25 | Poor |
| Maintenance Pulse | 45 | Fair |
| Dependency Health | 30 | Poor |
| License Clarity | — | Poor |
| Version Hygiene | — | Poor |
Analyzed 1 month ago
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