Knowledge RAG LLMs don't know your docs. Every conversation starts from zero. Your notes, writeups, internal procedures, PDFs — none of it exists to your AI assistant. Cloud RAG solutions leak your private data. Local ones require Docker, Ollama, and 15 minutes of setup before a single query. Knowledge RAG fixes this. One , zero external servers. Your documents become instantly searchable inside Claude Code — with reranking precision that actually finds what you need. 12 MCP Tools | Hybrid Search + Cross-Encoder Reranking
| Stars | 96 |
| Forks | 17 |
| Language | Python |
| Category | MCP 服务器 |
| License | MIT |
| Quality Score | 55.19/100 |
| Open Issues | 1 |
| Last Updated | 2026-06-16 |
| Created | 2026-02-05 |
| Platforms | claude-code, cli, codex, mcp, python |
| Est. Tokens | ~25k |
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knowledge-rag is [knowledge-rag] - Drop docs, search instantly from Claude Code — 12 MCP tools, 20 format parsers, hybrid search + reranking. Zero servers, zero API keys, 100% local.. It is categorized as a MCP 服务器 with 96 GitHub stars.
knowledge-rag is primarily written in Python. It covers topics such as antigravity, claude, claude-code.
You can find installation instructions and usage details in the knowledge-rag GitHub repository at github.com/lyonzin/knowledge-rag. The project has 96 stars and 17 forks, indicating an active community.
knowledge-rag is released under the MIT license, making it free to use and modify according to the license terms.