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 simonlin1212 · MCP Server · ★ 2.5k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Vibe-Research safe to install? View the security audit →
Vibe-Research · 个人 AI 投研系统(A股/美股/港股) 🌐 官网 · 产品预览 · 功能 · 数据源 · 快速开始 · 接入 AI · 合规 · 相关生态 · 联系作者 Vibe-Research: Your Personal Trading Research Agent · A股 / 美股 / 港股 的个人投研 Agent。 每日复盘、资讯雷达、个股数据、板块中心、我的持仓、研究记录。把数据和功能配齐,由你自己的 AI 驱动投资研究。 Vibe-Research 是一个开源的「个人 AI 投研看板」,主推 A 股、兼看美股 / 港股(A 股常要看隔夜外围脸色,数据配上更全)。它不替你做决定——把行情、研报、估值、财务、公告、资金面、资讯都配齐,放进一个干净的看板,再留一个能接入你自己的 AI 的接口。方向和结论,交给你自己配置的模型 / agent。 Vibe-Research: Your Personal Trading Research Agent. An open dashboard for China A-share (plus US / HK): it wires up all the data and plugs into your own AI / agent — it never recommends a stock. You bring the model, it brings the data. 🖥️
| Stars | 2,530 |
| Forks | 517 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 62.9633693243167/100 |
| Open Issues | 2 |
| Last Updated | 2026-09-20 |
| Created | 2026-07-05 |
| Platforms | codex, mcp, node |
| Est. Tokens | ~16k |
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Vibe-Research is Vibe-Research: Your Personal Trading Research Agent · A股/美股/港股 的个人投研 Agent:每日复盘、资讯雷达、个股数据、板块中心、我的持仓、研究记录、回测。Vibe-Research 把数据和功能配齐,由你自己的 Agent 驱动投资研究。基于开源的 Codex Harness 打造。. It is categorized as a MCP Server with 2.5k GitHub stars.
Vibe-Research is primarily written in TypeScript. It covers topics such as a-stock, ai-agent, codex.
You can find installation instructions and usage details in the Vibe-Research GitHub repository at github.com/simonlin1212/Vibe-Research. The project has 2.5k stars and 517 forks, indicating an active community.
Vibe-Research is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Vibe-Research on Agent Skills Hub include maverick-mcp, valuecell, open-trading-api. 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: