by OpenBMB · MCP Server · ★ 5.7k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/OpenBMB/UltraRAG.git --depth 1
docker pull hdxin2002/ultrarag:v0.3.0-base-cpu # Base version (CPU)Taken from the project's README on GitHub. Check the security audit before running it.
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. Full audit →
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 | 5,739 |
| Forks | 459 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 63/100 |
| Open Issues | 17 |
| Last Updated | 2026-11-07 |
| Created | 2025-01-16 |
| Platforms | mcp, python |
| Est. Tokens | ~17k |
Less Code, Lower Barrier, Faster Deployment 简体中文 &n
Looking for a UltraRAG alternative? If you're comparing UltraRAG 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.
程序员鱼皮的 AI 资源大全 + Vibe Coding 零基础教程，分享 OpenClaw 保姆级教程、大模型玩法（DeepSeek / GPT / Gemini / Claude / GLM）、最新 AI 资讯、Pr
Local, open-source AI app builder for power users ✨ v0 / Lovable / Replit / Bolt alternative 🌟 Star if you li
Code search MCP for Claude Code. Make entire codebase the context for any coding agent.
AI Agent Engineering Platform built on an Open Source TypeScript AI Agent Framework
A programmable Mixture-of-Models router for heterogeneous LLM inference
Your agent in your terminal, equipped with local tools: writes code, uses the terminal, browses the web. Make
Explore other popular mcp server tools:
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: