LangExtract
Extracts structured information from unstructured text and URLs using Google's LangExtract library and Gemini models, maintaining precise source grounding that maps every extraction to its exact location in the original text for healthcare documents, legal contracts, research papers, and business in
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FastMCP server implementation by Larsen Weigle that provides structured information extraction from unstructured text using Google's LangExtract library and Gemini models. The server maintains persistent connections and intelligent caching for optimal performance in long-running environments like Claude Code, offering tools for text extraction, URL processing, result visualization, and file operations with precise source grounding that maps every extraction to its exact location in the original text. Built with server-side credential management and optimized for Google Gemini models (gemini-2.5-flash and gemini-2.5-pro), it serves use cases across healthcare document processing, legal contract analysis, research paper extraction, and business intelligence workflows where maintaining traceability between extracted structured data and source text is critical.
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