MedAdapt Content Server
A specialized 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.
README
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
- Clone the repository:
git clone https://github.com/ryoureddy/medadapt-content-server.git
cd medadapt-content-server
- Create a virtual environment (optional but recommended):
python -m venv .venv
source .venv/bin/activate # On Windows, use: .venv\Scripts\activate
- Install dependencies:
pip install -r requirements.txt
- Configure (optional):
- Get an NCBI API key for improved rate limits: https://ncbiinsights.ncbi.nlm.nih.gov/2017/11/02/new-api-keys-for-the-e-utilities/
- Create a
.envfile based on.env.example
Usage
Running the Server
python content_server.py
Integration with Claude Desktop
- Open Claude Desktop
- Go to Settings → Model Context Protocol → Add Server
- Configure with the following JSON in your
claude_desktop_config.jsonfile located in:- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
- macOS:
{
"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_PATHenvironment 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 filtersget_resource_content: Retrieve complete content for a specific resourceget_topic_overview: Generate comprehensive overview of a medical topicsuggest_learning_resources: Get personalized resource recommendationsimport_user_document: Upload user-provided learning materialsgenerate_learning_plan: Create structured learning plan with objectivesextract_article_key_points: Extract key findings from medical articles
Troubleshooting
Common Issues and Solutions
-
Database Connection Error
- Symptom:
sqlite3.OperationalError: unable to open database file - Solution: Make sure the
DB_PATHenvironment variable is set correctly in your Claude Desktop configuration, pointing to an absolute path where the application has write permissions.
- Symptom:
-
File Path Error
- Symptom:
No such file or directoryerrors - Solution: Ensure all paths in the Claude Desktop configuration are absolute paths without extra quotes or escape characters.
- Symptom:
-
API Rate Limiting
- Symptom: Slow or failed responses from PubMed or NCBI Bookshelf
- Solution: Get an NCBI API key and add it to your
.envfile
-
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
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