awesome-llm-rag
github.com/jxzhangjhu/awesome-llm-rag ↗Awesome-LLM-RAG: a curated list of advanced retrieval augmented generation (RAG) in Large Language Models
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me rag long-text and memory resources from awesome-llm-rag"
Installation instructions →What's inside
RAG Long-text and Memory
- Agent Brain
7-layer cognitive memory system for AI agents with perception gate, dream cycle, and predictive capabilities. Built with FastAPI, PostgreSQL/pgvector. Self-hostable.
- Cortex
Persistent AI memory for coding assistants. Auto-captures decisions, patterns, and context. VSCode extension + CLI + MCP server. Free.
- Statewave
Open-source memory runtime for AI agents. Compiles events into deterministic, provenance-tagged context bundles instead of query-time retrieval. Apache-2.0, self-hostable on Postgres + pgvector.
Workshops and Tutorials
- Agent Shadow Brain
Self-evolving AI coding intelligence with infinite memory (TurboQuant), genetic algorithm self-evolution, predictive bug detection, PageRank knowledge graphs, swarm intelligence, and adversarial defense.
- Omni Skills Forge
50,000+ curated AI agent skills for Claude Code, Cursor, Copilot, Windsurf, Cline. Visual dashboard, one-click install, skill doctor, auto-update.
- RAG Techniques
35+ runnable Jupyter-notebook tutorials covering advanced RAG techniques: chunking, query transformation/HyDE, reranking, self-RAG, graph RAG, and evaluation.
RAG Search
- Not Human Search
Search engine and MCP server for discovering AI-native tools. 8,600+ sites indexed with agentic capability scoring. Useful for RAG pipelines that need to discover and integrate AI tools.
Showing a sample of 7 resources. View the full list on GitHub →