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MedAdapt Content Server

by ryoureddy
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Python
MIT License
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local-only server

The server can only run on the client’s local machine because it depends on local resources.

Integrations

  • Supports configuration through environment variables, including NCBI API keys for improved PubMed access rates.

  • Fetches and processes medical educational resources from PubMed, enabling search, retrieval, and analysis of medical research articles.

  • Uses SQLite database to store and manage medical content, topic mappings, and user documents.

MedAdapt Content Server

A specialized Model Context Protocol (MCP) server for Claude Desktop that enhances AI-assisted medical learning by fetching and processing educational resources from PubMed, NCBI Bookshelf, and user-provided documents.

Overview

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.

Quick Start

# Clone the repository git clone https://github.com/ryoureddy/medadapt-content-server.git cd medadapt-content-server # Install dependencies pip install -r requirements.txt # Run the server python content_server.py

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
  • Content Analysis: Extract key points, methodologies, and findings from medical resources
  • User Content: Import and analyze user-provided documents

Installation

Standard Installation

  1. Clone the repository:
git clone https://github.com/ryoureddy/medadapt-content-server.git cd medadapt-content-server
  1. Create a virtual environment (optional but recommended):
python -m venv .venv source .venv/bin/activate # On Windows, use: .venv\Scripts\activate
  1. Install dependencies:
pip install -r requirements.txt
  1. Configure (optional):

Usage

Running the Server

python content_server.py

Integration with Claude Desktop

  1. Open Claude Desktop
  2. Go to Settings → Model Context Protocol → Add Server
  3. Configure with the following JSON in your claude_desktop_config.json file located in:
    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    • Windows: %APPDATA%\Claude\claude_desktop_config.json
{ "mcpServers": { "medadapt": { "command": "/path/to/python", "args": [ "/path/to/medadapt-content-server/content_server.py" ], "env": { "DB_PATH": "/path/to/medadapt-content-server/medadapt_content.db" } } } }

Replace /path/to/python with your actual Python path (e.g., /opt/anaconda3/bin/python or C:\Python311\python.exe). Replace /path/to/medadapt-content-server/ with the absolute path to your cloned repository.

Important: The DB_PATH environment variable ensures the database file is created and accessed with an absolute path, preventing common file access errors.

Populating Initial Topic Mappings

python populate_topics.py

Testing

Run tests to verify everything is working:

python test_server.py

Example Usage with Claude

Scenario 1: Learning About a Medical Topic

User prompt to Claude:

I'd like to learn about the cardiac cycle. Can you provide a big picture overview and help me understand the key concepts?

Scenario 2: Finding Specific Resources

User prompt to Claude:

I need to find recent research articles about COVID-19 treatment options. Can you help me find relevant resources?

Scenario 3: Creating a Learning Plan

User prompt to Claude:

I'm a second-year medical student studying neurology. Can you create a learning plan for understanding stroke pathophysiology?

Available Tools

The server provides the following tools to Claude:

  • search_medical_content: Search for medical content with filters
  • get_resource_content: Retrieve complete content for a specific resource
  • get_topic_overview: Generate comprehensive overview of a medical topic
  • suggest_learning_resources: Get personalized resource recommendations
  • import_user_document: Upload user-provided learning materials
  • generate_learning_plan: Create structured learning plan with objectives
  • extract_article_key_points: Extract key findings from medical articles

Troubleshooting

Common Issues and Solutions

  1. Database Connection Error
    • Symptom: sqlite3.OperationalError: unable to open database file
    • Solution: Make sure the DB_PATH environment variable is set correctly in your Claude Desktop configuration, pointing to an absolute path where the application has write permissions.
  2. File Path Error
    • Symptom: No such file or directory errors
    • Solution: Ensure all paths in the Claude Desktop configuration are absolute paths without extra quotes or escape characters.
  3. API Rate Limiting
    • Symptom: Slow or failed responses from PubMed or NCBI Bookshelf
    • Solution: Get an NCBI API key and add it to your .env file
  4. Claude Desktop Connection
    • Symptom: Claude cannot connect to the MCP server
    • Solution: Verify the server is running in a terminal window and properly configured in Claude Desktop

Project Structure

medadapt-content-server/ │ ├── content_server.py # Main MCP server implementation ├── database.py # SQLite database interface ├── pubmed_utils.py # PubMed API utilities ├── bookshelf_utils.py # NCBI Bookshelf utilities ├── populate_topics.py # Script to populate initial topic data ├── test_server.py # Test script ├── requirements.txt # Python dependencies ├── .env.example # Example environment variables └── README.md # Documentation

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

  • NCBI for providing access to PubMed and Bookshelf APIs
  • Anthropic for Claude and the MCP integration capability

This server cannot be installed

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security - not tested
A
license - permissive license
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quality - not tested

A specialized Model Context Protocol server that enhances AI-assisted medical learning by connecting Claude Desktop to PubMed, NCBI Bookshelf, and user documents for searching, retrieving, and analyzing medical education content.

  1. Overview
    1. Quick Start
      1. Features
        1. Installation
          1. Standard Installation
        2. Usage
          1. Running the Server
          2. Integration with Claude Desktop
          3. Populating Initial Topic Mappings
          4. Testing
        3. Example Usage with Claude
          1. Scenario 1: Learning About a Medical Topic
          2. Scenario 2: Finding Specific Resources
          3. Scenario 3: Creating a Learning Plan
        4. Available Tools
          1. Troubleshooting
            1. Common Issues and Solutions
          2. Project Structure
            1. License
              1. Acknowledgments
                ID: kf16vbveq1