LangExtract MCP Server

Example Use Cases

• 1

  Extract structured information such as medications, dosages, and treatment protocols from clinical notes and research papers.

• 2

  Analyze legal and compliance documents by extracting contract terms, parties, and obligations.

• 3

  Process academic papers, survey responses, and business intelligence reports to extract methodologies, findings, and insights.

Description

The LangExtract MCP Server exposes the LangExtract Python library capabilities through the Model Context Protocol, allowing AI assistants to extract structured data from text documents with precise source grounding. It supports Google Gemini models with features like intelligent caching, persistent connections, and server-side credential management for optimal performance. This server is ideal for long-running environments and integrates seamlessly with Claude Code.