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.
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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.
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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.
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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.
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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
- 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 inpubmearch/resultsdirectory, logs inpubmed_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.