JackKuo666/PubMed-MCP-Server

🔍 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.
🤝 Contribute • 📝 Report Bug
✨ 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:
claude
Cursor
Paste the following into Settings → Cursor Settings → MCP → Add new server:
- Mac/Linux
Windsurf
CLine
1. Clone the repository:
2. Install the required dependencies:
📊 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:
1. search_pubmed_key_words: Search for articles on PubMed using keywords.
2. search_pubmed_advanced: Perform an advanced search for articles on PubMed with multiple parameters.
3. get_pubmed_article_metadata: Fetch metadata for a PubMed article using its PMID.
4. download_pubmed_pdf: Attempt to download the full-text PDF for a PubMed article.
5. 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