Enable AI assistants to search, access, and analyze PubMed articles through a simple MCP interface.
The PubMed MCP Server provides a bridge between AI assistants and PubMed's vast repository of biomedical literature through the Model Context Protocol (MCP). It allows AI models to search for scientific articles, access their metadata, and perform deep analysis in a programmatic way.
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Core Features
Paper Search: Query PubMed articles with keywords or advanced search
Efficient Retrieval: Fast access to paper metadata
Metadata Access: Retrieve detailed metadata for specific papers
Research Support: Facilitate biomedical sciences research and analysis
Paper Access: Attempt to download full-text PDF content
Deep Analysis: Perform comprehensive analysis of papers
Research Prompts: A set of specialized prompts for paper analysis
Quick Start
Prerequisites
Python 3.10+
FastMCP library
Installation
Installing via Smithery
To install pubmed-mcp-server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@JackKuo666/pubmed-mcp-server):
claude
Cursor
Paste the following into Settings Cursor Settings MCP Add new server:
Mac/Linux
Windsurf
CLine
Clone the repository:
```
git clone https://github.com/JackKuo666/PubMed-MCP-Server.git
cd PubMed-MCP-Server
```
Install the required dependencies:
```
pip install -r requirements.txt
```
Usage
Start the MCP server:
Usage with Claude Desktop
Add this configuration to your `claude_desktop_config.json`:
(Mac OS)
(Windows version):
Using with Cline
MCP Tools
The PubMed MCP Server provides the following tools:
`search_pubmed_key_words`: Search for articles on PubMed using keywords.
`search_pubmed_advanced`: Perform an advanced search for articles on PubMed with multiple parameters.
`get_pubmed_article_metadata`: Fetch metadata for a PubMed article using its PMID.
`download_pubmed_pdf`: Attempt to download the full-text PDF for a PubMed article.
`deep_paper_analysis`: Perform a comprehensive analysis of a PubMed article.
Searching Papers
You can ask the AI assistant to search for papers using queries like:
Getting Paper Details
Once you have a PMID, you can ask for more details:
Analyzing Papers
You can request a deep analysis of a paper:
Project Structure
`pubmed_server.py`: The main MCP server implementation using FastMCP
`pubmed_web_search.py`: Contains the logic for searching PubMed and retrieving article information
Dependencies
Python 3.10+
FastMCP
asyncio
logging
requests
beautifulsoup4
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
This project is licensed under the MIT License.
Disclaimer
This tool is for research purposes only. Please respect PubMed's terms of service and use this tool responsibly.