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 Miasyster · MCP Server · ★ 428
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is QuantGPT safe to install? View the security audit →
QuantGPT Agent-Driven Factor Research Engine — Autonomous Mining, Independent Validation on QuantGPT Cloud LLM Agent 自治因子挖矿 → 批量回测 → 多维评分 → 反过拟合验证 → QuantGPT Cloud 独立验证 + 样本外跟踪 | 全程零人工干预 Quick Start · Architecture · API Docs · MCP Guide · Factor Mining · Roadmap · Contributing WeChat / 微信交流群: Add on WeChat to join the community What Is QuantGPT QuantGPT is an agent-driven factor research engine — not a backtest library, not a chatbot wrapper. It gives an LLM Agent (Claude, via MCP) a complete toolkit to autonom
| Stars | 428 |
| Forks | 114 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 59.6798182118264/100 |
| Open Issues | 3 |
| Last Updated | 2026-05-20 |
| Created | 2026-03-20 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~497k |
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QuantGPT is Agent-driven alpha factory — LLM autonomously designs, backtests, and submits factors to WorldQuant BRAIN. It is categorized as a MCP Server with 428 GitHub stars.
QuantGPT is primarily written in Python. It covers topics such as a-shares, ai-agent, alpha.
You can find installation instructions and usage details in the QuantGPT GitHub repository at github.com/Miasyster/QuantGPT. The project has 428 stars and 114 forks, indicating an active community.
QuantGPT is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to QuantGPT on Agent Skills Hub include CNEquity, maverick-mcp, wcgw. 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: