No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by Sibyl-Research-Team · MCP Server · ★ 165
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is sibyl-research-system safe to install? View the security audit →
Sibyl Research System Fully Autonomous AI Scientist · From Idea to Paper, Zero Human Intervention Multi-Agent Scientific Discovery · GPU Experiment Execution · Self-Evolving Research Pipeline Inspired by the pioneering work of The AI Scientist, FARS, and AutoResearch, Sibyl takes the vision further by building natively on Claude Code to fully leverage its agent ecosystem — skills, plugins, MCP servers, and multi-agent teams. 中文文档 Sibyl is a fully autonomous AI scientist that drives end-to-end ML research — from literature survey and hypothesis generation to GPU experiment execution and conferen
| Stars | 165 |
| Forks | 20 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 61.1412856473925/100 |
| Last Updated | 2026-03-17 |
| Created | 2026-03-08 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~1415k |
These tools work well together with sibyl-research-system for enhanced workflows:
Looking for a sibyl-research-system alternative? If you're comparing sibyl-research-system 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.
900+ pure-markdown skills for autonomous AI research, organized as 9 freely-composable packages over a 4-layer
De-Anthropocentric Research Engine — AI-powered academic research automation with deep literature survey, gap
A curated hub of autonomous-research skills & agents — from idea to paper, on autopilot. | 自主科研技能与智能体精选库 —— 从灵
Don't trust an autoresearch paper at face value. Reviewer-side integrity forensics (self-consistency + fabrica
Multi-agent team operating system for Claude Code. 108 MCP tools, 40+ agent templates, 10 lifecycle hooks, 7 p
Open-source agent skills for AI for Science: topic exploration, literature survey, experiments, paper writing,
Explore other popular mcp server tools:
sibyl-research-system is Fully Autonomous AI Research System with Self-Evolution, built natively on Claude Code. It is categorized as a MCP Server with 165 GitHub stars.
sibyl-research-system is primarily written in Python. It covers topics such as ai-agent, ai-for-science, ai-scientist.
You can find installation instructions and usage details in the sibyl-research-system GitHub repository at github.com/Sibyl-Research-Team/sibyl-research-system. The project has 165 stars and 20 forks, indicating an active community.
The top alternatives to sibyl-research-system on Agent Skills Hub include de-anthropocentric-research-engine, De-Anthropocentric-Research-Engine, Auto-Research-Skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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: