PubMed MCP Server
About
A Model Context Protocol (MCP) server that enables AI assistants to search and analyze PubMed medical literature with advanced filtering, citations, and research tools.
Details
- License
- MIT
Explore
- Advanced PubMed Search: Search with complex filters including date ranges, article types, authors, journals, and MeSH terms
- Article Details: Retrieve detailed information for specific PMIDs including abstracts, authors, and metadata
- Citation Export: Export citations in multiple formats (BibTeX, APA, MLA, Chicago, Vancouver, EndNote, RIS)
- Author Search: Find articles by specific authors with co-author information
- Related Articles: Discover articles related to a specific PMID
- MeSH Term Search: Search and explore Medical Subject Headings
- Journal Analysis: Get metrics and recent articles from specific journals
- Research Trends: Analyze publication trends over time
- Article Comparison: Compare multiple articles side by side
- Caching: Built-in caching for improved performance
- Rate Limiting: Respectful API usage with configurable rate limits
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
PubMed MCP ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
- Python 3.8 or higher
- NCBI API key (free registration required)
- Valid email address for NCBI API identification
For development with additional tools:
make install-dev
Or manually:
pip install -r requirements.txt
pip install -e .
pip install black isort mypy flake8
1. Visit NCBI Account Settings
2. Sign in or create an account
3. Navigate to "API Key Management"
4. Create a new API key
5. Copy the key to your .env file
import asyncio
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client
async def main():
server_params = StdioServerParameters(
command="python",
args=["-m", "src.main"]
)
async with stdio_client(server_params) as (read, write):
async with ClientSession(read, write) as session:
make docker-run PUBMED_API_KEY=your_key PUBMED_EMAIL=your_email
```
The server provides the following MCP tools:
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"pubmed mcp server": {
"pubmed-mcp": {
"command": "python",
"args": [
"-m",
"src.main"
]
}
}
}
}McpServers
{
"pubmed-mcp": {
"command": "python",
"args": [
"-m",
"src.main"
]
}
}
A comprehensive Model Context Protocol (MCP) server for PubMed literature search and management. This server provides advanced search capabilities, citation formatting, and research analysis tools through the MCP protocol.
<a href="https://glama.ai/mcp/servers/@chrismannina/pubmed-mcp">
</a>
Features
- Advanced PubMed Search: Search with complex filters including date ranges, article types, authors, journals, and MeSH terms
- Article Details: Retrieve detailed information for specific PMIDs including abstracts, authors, and metadata
- Citation Export: Export citations in multiple formats (BibTeX, APA, MLA, Chicago, Vancouver, EndNote, RIS)
- Author Search: Find articles by specific authors with co-author information
- Related Articles: Discover articles related to a specific PMID
- MeSH Term Search: Search and explore Medical Subject Headings
- Journal Analysis: Get metrics and recent articles from specific journals
- Research Trends: Analyze publication trends over time
- Article Comparison: Compare multiple articles side by side
- Caching: Built-in caching for improved performance
- Rate Limiting: Respectful API usage with configurable rate limits
Installation
Prerequisites
- Python 3.8 or higher
- NCBI API key (free registration required)
- Valid email address for NCBI API identification
Quick Start
1. Clone the repository:
git clone https://github.com/your-org/pubmed-mcp.git
cd pubmed-mcp
2. Install dependencies:
pip install -r requirements.txt
3. Set up environment variables:
cp env.example .env
# Edit .env with your NCBI API key and email
4. Run the server:
python -m src.main
Development Installation
For development with additional tools:
make install-dev
Or manually:
pip install -r requirements.txt
pip install -e .
pip install black isort mypy flake8
Configuration
Create a .env file in the project root with the following variables:
```env
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