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Apple Docs

Provides an AI-powered semantic search engine for Apple's technical documentation, leveraging an in-memory knowledge graph for understanding and retrieval.

소개

This tool creates a local-first, in-memory knowledge graph and search index from Apple's developer documentation. It offers fast search capabilities, combining BM25 lexical ranking with optional semantic recall via Ollama embeddings, all without requiring an external database or internet connection for core functionality. Designed to be assistant-ready, it provides an MCP SSE server with tools for efficient searching, browsing, and generating grounded answers with citations, making Apple's vast documentation easily accessible offline.

주요 기능

  • 1 GitHub stars
  • Offline friendly, requiring no external database or internet for core usage.
  • Provides grounded answers with citations from the documentation.
  • Fast search combining BM25 lexical ranking with optional semantic recall via Ollama embeddings.
  • Assistant-ready MCP SSE server with tools for search, browsing, and one-shot answers.
  • Local-first, in-memory knowledge graph and search index from Apple docs exporter JSON.

사용 사례

  • Building custom applications that require deep, intelligent understanding and retrieval from structured technical content.
  • Developing AI assistants or chatbots capable of retrieving accurate information from Apple's technical documentation.
  • Enabling offline semantic search and access to Apple developer documentation for enhanced productivity.
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