Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@LightRAG MCPSearch for technical documentation on how the TMS module works"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
LightRAG MCP Server
English
A Model Context Protocol (MCP) server that provides a bridge to the LightRAG knowledge base. This allows AI assistants like Claude to query your technical documentation directly.
Features
Knowledge Base Querying: Access your private documents through LightRAG.
Language Support: Built-in support for Traditional Chinese and English.
Flexible Modes: Support for
hybrid,naive,local, andglobalretrieval modes.Easy Configuration: Simple environment variable setup.
Quick Start
Installation
python -m venv venv source venv/bin/activate # Windows: venv\Scripts\activate pip install -r requirements.txtConfiguration Copy
.env.exampleto.envand set:LIGHTRAG_URL: Your LightRAG backend URL.LIGHTRAG_LANG: Default language (zhoren).
Run
python lightrag_mcp.py
Tool: query_knowledge_base
query(string): Search query.mode(string):hybrid(default),naive,local,global.lang(string):zh(Traditional Chinese) oren(English).
正體中文
基於 Model Context Protocol (MCP) 的伺服器,作為 LightRAG 知識庫的橋樑。讓 AI 助手(如 Claude)可以直接查詢您的技術文件。
核心功能
知識庫查詢:透過 LightRAG 存取您的私有文件。
多語言支援:內建支援正體中文與英文。
靈活模式:支援
hybrid、naive、local與global檢索模式。簡易配置:透過環境變數輕鬆設定。
快速啟動
安裝
python -m venv venv source venv/bin/activate # Windows: venv\Scripts\activate pip install -r requirements.txt配置 複製
.env.example為.env並設定:LIGHTRAG_URL: LightRAG 後端 URL。LIGHTRAG_LANG: 預設語言 (zh或en)。
執行
python lightrag_mcp.py
工具:query_knowledge_base
query(字串):查詢字句或問題。mode(字串):檢索模式,可選hybrid(預設),naive,local,global。lang(字串):語言切換,可選zh(正體中文) 或en(英文)。
Development / 開發規範
See AGENTS.md for detailed guidelines. / 請參閱 AGENTS.md 了解詳細開發規範。
License
MIT
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Resources
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