PubMed Enhanced Search Server

Name: PubMed Enhanced Search Server
Author: leescot

@leescot

代码仓库

关于 PubMed Enhanced Search Server

pubmed-mcp-smithery

#pubmed #mcp #academic-research

基本信息

分类

数据与分析

运行时

python

传输方式

stdio

发布者

leescot

提交者

坤峰李

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "pubmed-mcp-smithery": {
      "command": "npx",
      "args": [
        "-y",
        "@smithery/cli@latest",
        "run",
        "@leescot/pubmed-mcp-smithery",
        "--config",
        "\"{}\""
      ]
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is PubMed Enhanced Search Server?

A Model Context Protocol (MCP) server that provides tools to search and retrieve academic papers from the PubMed database. It includes enhanced features such as MeSH term lookup, publication count statistics, and PICO-based evidence search. Designed for researchers, clinicians, and anyone conducting medical literature reviews.

How to use PubMed Enhanced Search Server?

Install Python 3.6+, fastmcp, and requests; then clone the repository and start the server with python pubmed_enhanced_mcp_server.py or in development mode with mcp dev pubmed_enhanced_mcp_server.py. Add the server to Claude Desktop by editing the claude_desktop_config.json file with the server's command and path.

Key features of PubMed Enhanced Search Server

Search PubMed by keywords with optional journal filter
Sort results by relevance or date (newest/oldest)
Look up MeSH terms related to a medical concept
Get publication counts for multiple search terms
Retrieve detailed paper info including abstract, DOI, authors
Perform structured PICO searches with synonym support

Use cases of PubMed Enhanced Search Server

Conduct literature searches for systematic reviews
Compare publication prevalence across multiple medical topics
Perform structured evidence-based searches using the PICO framework
Retrieve detailed metadata and abstracts for specific papers by PMID

FAQ from PubMed Enhanced Search Server

What are the prerequisites to run the server?

Python 3.6 or later and pip. The dependencies fastmcp and requests must be installed via pip.

How do I install the server?

Clone the repository, then run pip install fastmcp requests in the project directory.

What MCP functions does the server provide?

Five functions: search_pubmed, get_mesh_terms, get_pubmed_count, format_paper_details, and pico_search. Each accepts specific parameters and returns structured data.