medadapt-content-server

medadapt-content-server

3.3

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MedAdapt Content Server is a specialized MCP server for Claude Desktop, enhancing AI-assisted medical learning by fetching and processing educational resources from PubMed, NCBI Bookshelf, and user-provided documents.

The MedAdapt Content Server integrates with Claude Desktop to provide tools for searching, retrieving, and analyzing medical education content. It serves as a bridge between Claude and medical knowledge sources, allowing for enhanced AI-assisted learning experiences. By leveraging resources from PubMed, NCBI Bookshelf, and user documents, the server offers comprehensive content search, resource retrieval, and topic overviews. It also suggests learning resources and creates structured learning plans tailored to the user's educational level. The server's capabilities extend to content analysis, extracting key points and methodologies from medical resources, and importing user-provided documents for further analysis. This integration aims to facilitate a more interactive and informed learning process for medical students and professionals.

Features

  • Content Search: Search for medical educational content across multiple sources
  • Resource Retrieval: Fetch complete articles, book chapters, and user documents
  • Topic Overviews: Generate comprehensive overviews of medical topics
  • Learning Resources: Suggest appropriate learning resources based on topic and student level
  • Learning Plans: Create structured learning plans with objectives and resources

Tools

  1. search_medical_content

    Search for medical content (with filters)

  2. get_resource_content

    Search the complete content of a specific resource

  3. get_topic_overview

    A comprehensive overview of generative medical topics

  4. suggest_learning_resources

    Get personalized resource recommendations

  5. import_user_document

    Upload learning materials provided by users

  6. generate_learning_plan generate_learning_plan

    Create a structured learning plan

  7. extract_article_key_points

    Extract key findings from medical articles