工具说明为英文。
RAG 与搜索
检索增强、向量数据库、嵌入和语义搜索。
用途
活跃度
排序方式
139
工具排名
Ranked by known GitHub stars, highest first; archived repositories come after maintained repositories. 原始值保留各自的数据窗口;计算变化需要 7 天内至少两次测量。
- 1788 3517 天下载量+62 634 (+8.6 %)
- 21 882 0367 天下载量-127 698 (-6.4 %)
- 35 343 8597 天下载量+30 602 (+0.58 %)
学习与参考资源
Ranked by known GitHub stars, highest first; archived repositories come after maintained repositories. 这些资源可单独访问,不参与主要排名。
- 1活跃打开来源 ↗
Official Claude Documentation - Converted to 2000+ Markdown Files - All documentation sourced from first party sources- 24 categories - refreshed daily, multi-agent orchestration
github安装
资源实测增长/plugin marketplace add johnzfitch/claude-wiki21GitHub 星标稳定 - 2活跃打开来源 ↗
My complete journey to becoming an Agentic AI Engineer through structured learning, projects, experiments, and production-ready implementations of modern AI systems.
github资源实测增长18GitHub 星标稳定 - 3活跃打开来源 ↗
🤖 The strongest curated list of open-source AI-agent tools for literature review — 70+ tools across 11 categories (Claude Code skills, deep research, MCP servers, PDF parsing, systematic review). 面向智能体文献综述的最强工具大全。
github资源实测增长16GitHub 星标+2 (+14.3 %) - 4活跃打开来源 ↗
Spring AI 实战教程 🚀 ChatClient → RAG → MCP → Agent → A2A,24 个手写模块循序渐进(Spring Boot 4.1 + Spring AI 2.0 + Java 21)
github资源实测增长3GitHub 星标稳定 - 5活跃打开来源 ↗
Curated Agentic AI resources: AI agent frameworks, tutorials, courses, projects, MCP tools, research papers, evaluation, security, and production guides.
github资源实测增长2GitHub 星标稳定 - 6活跃打开来源 ↗
Detect underpriced products by scraping deals and using AI models to estimate fair prices for profit opportunity identification.
github资源实测增长1GitHub 星标稳定 - 7活跃打开来源 ↗
Handbook técnico aberto sobre engenharia de IA em produção: ML tradicional, LLMs, RAG, agentes, segurança, observabilidade, FinOps e deployment.
github资源实测增长1GitHub 星标稳定 - 8休眠打开来源 ↗
Interactive roadmap for becoming an Agentic AI Engineer — 11 stages from Python & FastAPI to multi-agent systems, MCP, RAG, Docker, and context engineering
github资源实测增长1GitHub 星标稳定 - 9活跃打开来源 ↗
Comprehensive collection of AI concepts, research findings, and practical implementations. From machine learning fundamentals to cutting-edge LLMs, agents, and emerging technologies.
github资源实测增长1GitHub 星标稳定 - 100GitHub 星标稳定
- 11休眠打开来源 ↗
50+ AI agent apps you can actually run — MCP, A2A, LangGraph, SAP, RAG, and multi-agent patterns
github资源估算动量0GitHub 星标·