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PubMed Analysis MCP Server

@Darkroaster

リポジトリ

PubMed Analysis MCP Server について

A PubMed MCP server.

基本情報

カテゴリ

データと分析

ライセンス

MIT

ランタイム

python

トランスポート

stdio

公開者

Darkroaster

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

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

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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.

コメント

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