What is medRxiv MCP Server?
The medRxiv MCP Server is a tool that enables AI assistants to search and access medRxiv papers through a simple Model Context Protocol (MCP) interface, facilitating access to health sciences preprints.
How to use medRxiv MCP Server?
To use the medRxiv MCP Server, install it via Smithery or manually, then start the server and configure it with your AI assistant to enable paper searches and access.
Key features of medRxiv MCP Server?
- Paper Search: Custom queries to find medRxiv papers.
- Efficient Retrieval: Quick access to paper metadata.
- Paper Access: Download and read paper content.
- Local Storage: Save papers for faster access.
- Research Prompts: Specialized prompts for paper analysis.
Use cases of medRxiv MCP Server?
- Searching for recent health sciences research papers.
- Accessing detailed information about specific papers using DOI.
- Analyzing academic papers with specialized prompts.
FAQ from medRxiv MCP Server?
- Can I search for any health sciences paper?
Yes, you can search for any paper available on medRxiv using custom queries.
- Is there a specific Python version required?
Yes, Python 3.10 or higher is required to run the server.
- How do I contribute to the project?
Contributions are welcome! You can submit a Pull Request on GitHub.
medRxiv MCP Server
🔍 Enable AI assistants to search and access medRxiv papers through a simple MCP interface.
The medRxiv MCP Server provides a bridge between AI assistants and medRxiv's preprint repository through the Model Context Protocol (MCP). It allows AI models to search for health sciences preprints and access their content in a programmatic way.
🤝 Contribute • 📝 Report Bug
✨ Core Features
- 🔎 Paper Search: Query medRxiv papers with custom search strings ✅
- 🚀 Efficient Retrieval: Fast access to paper metadata ✅
- 📄 Paper Access: Download and read paper content 📝
- 📋 Paper Listing: View all downloaded papers 📝
- 🗃️ Local Storage: Papers are saved locally for faster access 📝
- 📝 Research Prompts: A set of specialized prompts for paper analysis 📝
- 📊 Research Support: Facilitate health sciences research and analysis 📝
🚀 Quick Start
Installing via Smithery
To install medRxiv Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install medrxiv-mcp-server --client claude
Installing Manually
Install using uv:
uv tool install medRxiv-mcp-server
For development:
# Clone and set up development environment
git clone https://github.com/JackKuo666/medRxiv-MCP-Server.git
cd medRxiv-MCP-Server
# Create and activate virtual environment
uv venv
source .venv/bin/activate
uv pip install -r requirements.txt
📊 Usage
Start the MCP server:
python medrxiv_server.py
🛠 MCP Tools
Usage with Claude Desktop
Add this configuration to your claude_desktop_config.json
:
(Mac OS)
{
"mcpServers": {
"biorxiv": {
"command": "python",
"args": ["-m", "medrxiv-mcp-server"]
}
}
}
(Windows version):
{
"mcpServers": {
"biorxiv": {
"command": "C:\\Users\\YOUR_USERNAME\\AppData\\Local\\Programs\\Python\\Python311\\python.exe",
"args": [
"-m",
"medrxiv-mcp-server"
]
}
}
}
Using with Cline
{
"mcpServers": {
"medrxiv": {
"command": "bash",
"args": [
"-c",
"source /home/YOUR/PATH/mcp-server-bioRxiv/.venv/bin/activate && python /home/YOUR/PATH/mcp-server-bioRxiv/medrxiv_server.py"
],
"env": {},
"disabled": false,
"autoApprove": []
}
}
}
After restarting Claude Desktop, the following capabilities will be available:
Searching Papers
You can ask Claude to search for papers using queries like:
Can you search bioRxiv for recent papers about genomics?
The search will return basic information about matching papers including:
• Paper title
• Authors
• DOI
Getting Paper Details
Once you have a DOI, you can ask for more details:
Can you show me the details for paper 10.1101/003541?
This will return:
• Full paper title
• Authors
• Publication date
• Paper abstract
• Links to available formats (PDF/HTML)
📝 TODO
download_paper
Download a paper and save it locally.
read_paper
Read the content of a downloaded paper.
list_papers
List all downloaded papers.
📝 Research Prompts
The server offers specialized prompts to help analyze academic papers:
Paper Analysis Prompt
A comprehensive workflow for analyzing academic papers that only requires a paper ID:
result = await call_prompt("deep-paper-analysis", {
"paper_id": "2401.12345"
})
This prompt includes:
- Detailed instructions for using available tools (list_papers, download_paper, read_paper, search_papers)
- A systematic workflow for paper analysis
- Comprehensive analysis structure covering:
- Executive summary
- Research context
- Methodology analysis
- Results evaluation
- Practical and theoretical implications
- Future research directions
- Broader impacts
📁 Project Structure
medrxiv_server.py
: The main MCP server implementation using FastMCPmedrxiv_web_search.py
: Contains the web scraping logic for searching medRxiv
🔧 Dependencies
- Python 3.10+
- mcp[cli]>=1.4.1
- requests>=2.25.1
- beautifulsoup4>=4.9.3
🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
📄 License
This project is licensed under the MIT License.
🙏 Acknowledgements
This project is inspired by and built upon the work done in the arxiv-mcp-server project.
⚠️ Disclaimer
This tool is for research purposes only. Please respect medRxiv's terms of service and use this tool responsibly.