Wandering RAG is a command-line interface tool designed for personal Retrieval-Augmented Generation (RAG). It fetches data from various sources like Notion, Obsidian, and Apple Notes, stores it in Qdrant, and exposes it as an MCP server for easy access and querying.
Added on:
Created by:
Apr 25 2025
Wandering RAG is a command-line interface tool designed for personal Retrieval-Augmented Generation (RAG). It fetches data from various sources like Notion, Obsidian, and Apple Notes, stores it in Qdrant, and exposes it as an MCP server for easy access and querying.
Added on:
Created by:
Apr 25 2025
Yang Liu
Featured
What is Wandering RAG?
Wandering RAG is a versatile CLI tool that enables users to perform personal RAG tasks efficiently. It retrieves and indexes data from multiple personal knowledge base sources such as Notion, Obsidian, and Apple Notes, storing the information in Qdrant vector database. The tool exposes this stored data through an MCP (Multi-Channel Processing) server, allowing seamless querying and integration with other AI models like Claude Desktop. It simplifies the process of managing and accessing personal data for AI-assisted answering, research, and information retrieval, providing a powerful solution for knowledge management and AI interactions.
Who will use Wandering RAG?
- Individuals managing personal knowledge bases
- Researchers
- AI developers
- Productivity enthusiasts
How to use the Wandering RAG?
- Step1: Install the tool using uv pip install -e.
- Step2: Set up a Qdrant server by running docker-compose up -d.
- Step3: Configure the environment variables and specify data folders in the .env file.
- Step4: Use commands like ./wandering-rag md index or ./wandering-rag notion index to index sources.
- Step5: Run the MCP server with ./wandering-rag mcp run-server.
- Step6: Connect and query the data through the MCP server using desired AI models or interfaces.
Wandering RAG's Core Features & Benefits
The Core Features
- Retrieves data from Notion, Obsidian, Apple Notes
- Indexes data in Qdrant
- Exposes data as an MCP server
- Supports integration with AI models like Claude Desktop
The Benefits
- Makes personal knowledge easily accessible for AI querying
- Simplifies management of data across multiple sources
- Enables efficient retrieval-augmented generation for personalized data
- Supports customization and flexible data configuration
Wandering RAG's Main Use Cases & Applications
- Personal knowledge management and retrieval
- Enhancing AI chatbot responses with personal data
- Research and data analysis from multiple sources
- Productivity and note organization for researchers and enthusiasts
FAQs of Wandering RAG
Developer
- wandermyz
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