by franzvill · MCP Server · ★ 245
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 | 245 |
| Forks | 31 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 53/100 |
| Open Issues | 1 |
| Last Updated | 2026-07-01 |
| Created | 2026-01-28 |
| Platforms | mcp, python |
| Est. Tokens | ~13k |
Local Agent Discovery for A2A (LAD-A2A) An open protocol for discovering A2A-capable agents on local networks. LAD-A2A addresses a critical gap in the AI agent ecosystem: when a device joins a network—hotel Wi-Fi, office LAN, cruise ship, hospital campus—how does the user's AI assistant discover and connect to local agents? While A2A defines agent-to-agent communication and MCP defines...
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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: