Asset-Aware Medical MCP

Example Use Cases

• 1

  Analyze and retrieve precise assets (tables, figures, sections) from medical PDF documents.

• 2

  That require integration with a knowledge graph for cross-document comparison and reasoning.

• 3

  Edit and manage DOCX documents in markdown format with fidelity and table bridging.

Description

Asset-Aware MCP provides advanced PDF parsing with dual engines, enabling AI agents to access and analyze embedded assets like tables, figures, and sections in medical literature. It supports asynchronous job pipelines, document manifest navigation, and integrates a knowledge graph for cross-document reasoning. The system also offers docx editing in markdown format, table management tools, and a VS Code extension for graphical management, optimizing AI workflows in medical research.