Ragtag
Indexes local documents and runs Retrieval Augmented Generation (RAG) search to provide context for AI tools.
About
Ragtag is a simple, hacky MVP server designed to enable local Retrieval Augmented Generation (RAG) capabilities for AI assistants like Claude. It allows users to index their local codebases and documentation, creating a searchable vector database. This database can then be queried by an AI tool, feeding it relevant contextual information to improve its understanding and responses, especially useful for project-specific planning and code changes by leveraging local, custom knowledge.
Key Features
- Indexes local documents and codebases for RAG search
- Supports custom embedding and LLM models via Ollama
- Integrates as a Micro-Controller Protocol (MCP) server for AI tools
- Configurable multiple search indices
- Provides OSX-specific installation helper for Ollama and models
- 0 GitHub stars
Use Cases
- Enhancing AI assistant understanding of specific project codebases and documentation
- Enabling contextual AI responses for planning code changes within a project
- Providing proprietary or local document context to AI tools for development
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