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 Decade-qiu · MCP Server · ★ 601
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is CookHero safe to install? View the security audit →
智能烹饪与饮食管理助手 · 你的个性化饮食英雄 简体中文 | English 📖 项目简介 CookHero（烹饪英雄）是一个融合 LLM、RAG、Agent、多模态与营养数据分析的个性化饮食管理平台。它不仅是菜谱库，更是一位能陪你做计划、做记录、看数据、给建议的“饮食管理英雄助手”，帮助你把烹饪与健康目标变成可执行的日常。 🔍 智能问答：解答烹饪技巧、食材搭配、营养知识等问题 🍽️ 个性化推荐：根据口味、目标和限制提供更贴合的菜品选择 🗓️ 饮食计划：按周规划三餐与加餐，形成可执行的饮食节奏 🧾 AI 记录：文字/图片一键记录，自动估算热量与宏量营养 📊 营养分析：每日/每周统计与计划偏差分析，持续优化习惯 🧠 深度理解：多轮对话理解用户意图，输出精准行动建议 🌐 实时搜索：结合 Web 搜索获取最新烹饪资讯和趋势 CookHero 面向厨房新手、健身/减脂/控糖人群、健康饮食倡导者、过敏体质用户及家庭场
| Stars | 601 |
| Forks | 94 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 61.7394994579435/100 |
| Open Issues | 35 |
| Last Updated | 2026-08-21 |
| Created | 2025-11-29 |
| Platforms | browser, mcp, python |
| Est. Tokens | ~15k |
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CookHero is CookHero是一个基于 LLM + RAG + Agent + 多模态的智能饮食与烹饪管理平台，支持智能菜谱查询、个性化饮食计划、AI 饮食记录、营养分析、Web 搜索增强，以及可扩展的 ReAct Agent / Subagent 工具体系，帮助厨房新手轻松成为“烹饪英雄”。. It is categorized as a MCP Server with 601 GitHub stars.
CookHero is primarily written in Python. It covers topics such as agent, ai-chatbot, cooking-assistant.
You can find installation instructions and usage details in the CookHero GitHub repository at github.com/Decade-qiu/CookHero. The project has 601 stars and 94 forks, indicating an active community.
CookHero is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to CookHero on Agent Skills Hub include flock, EnterpriseAgentFramework, memsearch. 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: