by labsai · MCP Server · ★ 389
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
docker pull labsai/eddi # Pull latest from Docker HubTaken from the project's README on GitHub.
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 | 389 |
| Forks | 131 |
| Language | Java |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 64/100 |
| Open Issues | 92 |
| Last Updated | 2026-11-06 |
| Created | 2016-10-13 |
| Platforms | docker, java, mcp |
| Est. Tokens | ~25k |
E.D.D.I — Multi-Agent Orchestration Middleware for Conversational AI E.D.D.I (Enhanced Dialog Driven Interface) is a production-grade, config-driven multi-agent orchestration middleware for conversational AI. It coordinates users, AI agents, and business systems through intelligent routing, persistent memory, and API orchestration — without writing code. Built with Java 25 and Quarkus.
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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: