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PubMed Analysis MCP Server

@Darkroaster

Repository

Basic information

Category

Data & Analytics

License

MIT

Transports

stdio

Author

Darkroaster

About PubMed Analysis MCP Server

A PubMed MCP server.

#pubmed#mcp-server#medical-research

PubMed Analysis MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "pubmed-MCP-server": {
      "command": "uv",
      "args": [
        "pip",
        "install",
        "-r",
        "requirements.txt"
      ]
    }
  }
}

PubMed Analysis MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is PubMed Analysis MCP Server?

It is a professional MCP server that analyzes PubMed medical literature, helping researchers quickly gain insights into medical research dynamics. It provides tools for literature retrieval, hotspot analysis, trend tracking, and publication statistics.

How to use PubMed Analysis MCP Server?

Install dependencies with uv in the project directory, then configure the MCP client (e.g., in mcp.json) with the command to run the server and set the NCBI_USER_EMAIL and NCBI_USER_API_KEY environment variables. Communicate with the server via large language models, using the provided tools such as search_pubmed, analyze_research_keywords, and generate_comprehensive_analysis.

Key features of PubMed Analysis MCP Server

  • Literature retrieval with PubMed advanced search syntax and date filtering.
  • Hotspot analysis by keyword frequency to identify popular research areas.
  • Trend tracking of keyword frequency changes over time.
  • Publication count analysis with customizable time periods.
  • Comprehensive report generation with customizable parameters.

Use cases of PubMed Analysis MCP Server

  • Analyze research hotspots on a specific medical topic over a recent period.
  • Track the evolution of research trends for a given keyword over time.
  • Generate a comprehensive analysis report including hotspots, trends, and publication statistics.
  • Quickly obtain a summary of recent literature on a disease or treatment.

Frequently asked questions

1

What data sources does it use?

It queries PubMed, the National Library of Medicine's database of biomedical literature, and requires an NCBI API key and email.

2

How do I get an NCBI API key?

Log in to PubMed, go to Account Settings, scroll to the "API Keys" section, and click "Create API Key".

3

What are the runtime requirements?

It requires Python with uv (virtual environment) and the dependencies listed in `pyproject.toml`. The server runs locally.

4

Where are results saved?

Result files are saved in the `pubmearch/results` directory, and logs are stored in `pubmed_server.log`.

5

What transport or authentication does it use?

The server uses the MCP protocol; authentication is via the NCBI API key set in the `NCBI_USER_API_KEY` environment variable. No other transport or auth details are provided.

Comments

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