PubMed Analysis MCP Server

Name: PubMed Analysis MCP Server
Author: Darkroaster

@Darkroaster

代码仓库

关于 PubMed Analysis MCP Server

A PubMed MCP server.

基本信息

分类

数据与分析

许可证

MIT

运行时

python

传输方式

stdio

发布者

Darkroaster

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "pubmearch": {
      "command": "uv",
      "args": [
        "pip",
        "install",
        "-e",
        "."
      ]
    }
  }
}

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 Analysis MCP Server?

A professional MCP server for analyzing PubMed medical literature. It helps researchers quickly gain insights into medical research dynamics by supporting advanced search syntax, keyword frequency analysis, trend tracking, publication counts, and comprehensive report generation.

How to use PubMed Analysis MCP Server?

Install dependencies using uv pip install -e . in the pyproject.toml directory. Configure the MCP server in mcp.json with the command uv run --directory path/to/project -m pubmearch.server, and set environment variables NCBI_USER_EMAIL and NCBI_USER_API_KEY. Use the provided tools (e.g., search_pubmed, analyze_research_keywords) via LLM prompts.

Key features of PubMed Analysis MCP Server

Literature retrieval with PubMed advanced search syntax and date filtering.
Hotspot analysis: keyword frequency and popular research area identification.
Trend tracking: keyword frequency changes over time.
Publication count analysis with customizable time periods.
Comprehensive reports: one-click generation of hotspot, trend, and statistics.

Use cases of PubMed Analysis MCP Server

Identify research hotspots on a specific medical topic (e.g., prostate cancer immunotherapy).
Track how research trends evolve over custom date ranges.
Generate a full analytical report of publication volume and keyword dynamics.
Retrieve and save PubMed search results for offline review.

FAQ from PubMed Analysis MCP Server

What dependencies are required?

Python environment with uv is recommended. The server requires NCBI API credentials (NCBI_USER_EMAIL and NCBI_USER_API_KEY).

How are search results stored?

Results are saved in the pubmearch/results directory; logs are in pubmed_server.log.

What is the default maximum number of search results?

The default max_results for search_pubmed is 1000.

Is there any usage policy to follow?

Yes, you must follow NCBI's API usage policies.

What license does the project use?

MIT license.

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