by ybeven · MCP Server · ★ 182
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 182 |
| Forks | 19 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 76/100 |
| Last Updated | 2026-10-03 |
| Created | 2026-01-09 |
| Platforms | mcp, python |
| Est. Tokens | ~5k |
4D-ARE: Attribution-Driven Agent Requirements Engineering Build LLM agents that explain why, not just what. The Problem Your LLM agent has full data access and executes flawlessly. But when asked: "Why is our customer retention rate only 56%?" It returns a list of metrics instead of a causal explanation: This is the Attribution Gap - agents can report what happened, but struggle to explain why.
Looking for a 4D-ARE alternative? If you're comparing 4D-ARE with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
A handy lib for smooth interaction with large language models (LLMs) and crafting AI apps.
Stock market MCP server for Yahoo Finance data, technical analysis, portfolio tracking, and Python backtesting
Your personal AI assistant, running on your own computer. Long-running tasks, real memory, proactive help, voi
Official python implementation of UTCP. UTCP is an open standard that lets AI agents call any API directly, wi
🚀 Universal SDK for building next-gen MCP servers
🌐Web Agent Protocol (WAP) - Record and replay user interactions in the browser with MCP support
Explore other popular mcp server tools:
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: