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pubmearch

MCP.Pizza Chef: Darkroaster

Pubmearch is a specialized MCP server designed for in-depth analysis of PubMed medical literature. It supports advanced search syntax, keyword frequency analysis, trend tracking over time, and publication statistics. Researchers can generate comprehensive reports to quickly understand research hotspots and evolving trends in medical science, facilitating faster insights into the latest developments.

Use This MCP server To

Perform advanced PubMed literature searches with date and result filters Analyze keyword frequency to identify popular medical research topics Track changes in research trends over time using keyword trend analysis Generate publication count statistics over customizable time periods Create comprehensive reports summarizing hotspots, trends, and statistics

README

PubMed Analysis MCP Server

适用于PubMed的MCP server:这是一个刚刚开发的项目,功能仍在完善中,欢迎各位提出建议和改进!

Note: This is a newly developed project with features still being refined. Suggestions and improvements are welcome!

一个专业的PubMed医学文献分析MCP服务器,帮助科研人员快速洞察医学研究动态。

A professional MCP server for analyzing PubMed medical literature to help researchers quickly gain insights into medical research dynamics.

功能特点 / Features

  • 文献检索 / Literature Retrieval: 支持PubMed高级检索语法,可设置日期范围和结果数量。/ Supports PubMed advanced search syntax with date filtering.

  • 热点分析 / Hotspot Analysis: 统计关键词频率,识别热门研究方向,汇总相关文献。/ Analyzes keyword frequencies to identify popular research areas.

  • 趋势追踪 / Trend Tracking: 追踪关键词随时间的频率变化,揭示研究趋势演变。/ Tracks keyword changes over time to reveal evolving research trends.

  • 发文统计 / Publication Count: 提供灵活的时间周期设置,分析文献数量变化。/ Analyzes publication volume changes with customizable time periods.

  • 全面报告 / Comprehensive Reports: 一键生成包含热点、趋势和统计的分析报告。/ Generates complete reports with customizable parameters.

MCP工具 / MCP Tools

1. search_pubmed

搜索PubMed并保存结果。/ Search PubMed and save results.

主要参数 / Key parameters: 一般而言不需要显性设置,与大模型沟通即可。/ Generally, no need to set explicitly, communicate with large models.

  • advanced_search: PubMed搜索查询(必填,与高级检索语法相同)/ PubMed search query (required, same as advanced search syntax)
  • start_date: 开始日期(格式:YYYY/MM/DD)/ Start date (format: YYYY/MM/DD)
  • end_date: 结束日期(格式:YYYY/MM/DD)/ End date (format: YYYY/MM/DD)
  • max_results: 最大结果数(默认:1000)/ Maximum results (default: 1000)

2. list_result_files

列出可用的结果文件。/ List available result files.

3. analyze_research_keywords

分析研究热点以及研究趋势。/ Analyze research hotspots and research trends. 主要参数 / Key parameters:

  • top_n: 分析的关键词数量(默认:20)/ Number of keywords (default: 20)

4. analyze_publication_count

分析发文数量。/ Analyze publication counts.

5. generate_comprehensive_analysis

生成全面分析报告。/ Generate comprehensive analysis.

Trae使用示例 / Example for Trae

Between us... when I use the same model, Cursor makes me feel like I'm the one not making sense. Trae, on the other hand, just gets me. Seriously great IDE!

安装依赖 / Install Dependencies

推荐使用uv虚拟环境。/ Recommend using uv virtual environment.
uv:访问uv repo

# pyproject.toml 目录下:
uv pip install -e .

Write mcp.json

Merge the following configuration in mcp.json (for Windows):

{
  "mcpServers": {
    "pubmearch": {
      "command": "cmd",
      "args": [
        "/c",
        "uv",
        "run",
        "--directory",
        "path/to/project/root/directory",  // The folder where the pubmearch folder is located
        "-m",
        "pubmearch.server"
      ],
      "env": {
        "NCBI_USER_EMAIL": "youremailaddress@email.com",
        "NCBI_USER_API_KEY": "your_api_key"
      }
    }
  }
}

PubMed API key获取 / Get PubMed API key

  1. 登录PubMed网站。/ Log in to PubMed.
  2. 点击右上角的头像,选择“ Account Settings”。/ Click on your profile picture and select " Account Settings".
  3. 向下滚动到“API Keys”部分,点击“Create API Key”。/ Scroll down to the "API Keys" section and click "Create API Key".

LLM prompt (Agent mode)

推荐使用高级检索语法。/ Use advanced search syntax.

  • Help me analyze the research hotspots on prostate cancer immunotherapy in the past three months. The advanced search query is ((prostat*[Title/Abstract]) AND (cancer[Title/Abstract])) AND (immu*[Title/Abstract]).
  • 帮我分析一下近三个月前列腺癌免疫治疗的研究热点,检索词为((prostat*[Title/Abstract]) AND (cancer[Title/Abstract])) AND (immu*[Title/Abstract]).

注意事项 / Notes

  • 请遵循NCBI的API使用政策。/ Follow NCBI usage policies.
  • 结果文件保存在pubmearch/results目录,日志位于pubmed_server.log。/ Results saved in pubmearch/results directory, logs in pubmed_server.log.
  • 本人平时学业繁忙,项目可能会有延迟。/ I am busy with my studies, the project may be delayed.

贡献 / Contributions

欢迎通过Issue或Pull Request贡献改进。/ Contributions are welcome via Issues or Pull Requests.

许可证 / License

MIT

pubmearch FAQ

How does pubmearch support advanced PubMed searches?
It supports PubMed's advanced search syntax including date range and result count filters for precise literature retrieval.
Can pubmearch track research trends over time?
Yes, it analyzes keyword frequency changes over time to reveal evolving research trends.
What kind of reports can pubmearch generate?
It generates comprehensive reports that include hotspot analysis, trend tracking, and publication statistics.
Is pubmearch suitable for non-expert users?
While designed for researchers, its user-friendly interface and report generation make it accessible to a broad audience.
How can I contribute suggestions or improvements?
Since pubmearch is newly developed, contributions and feedback are welcome via its GitHub repository.
Does pubmearch support integration with other MCP clients?
Yes, as an MCP server, it can be integrated with various MCP clients for enhanced workflows.
What languages does pubmearch support?
The primary interface and documentation are in English and Chinese, supporting a wide user base.
How secure is the data handled by pubmearch?
It follows MCP principles for secure, scoped, and observable model interactions to protect user data.