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Nancy Brain

Transforms any GitHub repository into a searchable knowledge base for AI agents.

About

Nancy Brain is a lightweight Retrieval-Augmented Generation (RAG) backend that enables AI assistants to instantly access comprehensive knowledge from GitHub repositories and PDF articles. It indexes full source code, live documentation, and real examples (like Jupyter notebooks and test cases), making it searchable. The system includes smart weighting, ensuring important documents are prioritized, and offers both an HTTP API and a Model Context Protocol (MCP) server connector, alongside a user-friendly web administration interface for easy management and rapid prototyping.

Key Features

  • Convert GitHub repositories and PDF articles into searchable knowledge bases
  • Web Admin Interface for visual knowledge base management and testing
  • Dynamic weighting system to prioritize important documents and persist learning
  • 0 GitHub stars
  • Index full source code, documentation, examples, and notebooks
  • Provides HTTP API and Model Context Protocol (MCP) server connectors for AI assistants

Use Cases

  • Researchers building knowledge bases from scientific software and papers
  • Teams managing and accessing shared knowledge bases through a visual interface
  • ML Engineers creating searchable indexes from machine learning frameworks
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