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": "[email protected]",
        "NCBI_USER_API_KEY": "your_api_key"
      }
    }
  }
}

PubMed API key获取 / Get PubMed API key

登录PubMed网站。/ Log in to PubMed.
点击右上角的头像，选择“ Account Settings”。/ Click on your profile picture and select " Account Settings".
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

PubMed Analysis