PubMed-MCP-Server

🔍 Enable AI assistants to search, access, and analyze PubMed articles through a simple MCP interface.

The PubMed MCP Server provides a bridge between AI assistants and PubMed's vast repository of biomedical literature through the Model Context Protocol (MCP). It allows AI models to search for scientific articles, access their metadata, and perform deep analysis in a programmatic way.

🤝 Contribute • 📝 Report Bug

• 🔎 Paper Search: Query PubMed articles with keywords or advanced search ✅
• 🚀 Efficient Retrieval: Fast access to paper metadata ✅
• 📊 Metadata Access: Retrieve detailed metadata for specific papers ✅
• 📊 Research Support: Facilitate biomedical sciences research and analysis ✅
• 📄 Paper Access: Attempt to download full-text PDF content ✅
• 🧠 Deep Analysis: Perform comprehensive analysis of papers ✅
• 📝 Research Prompts: A set of specialized prompts for paper analysis ✅

• Python 3.10+
• FastMCP library

To install pubmed-mcp-server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @JackKuo666/pubmed-mcp-server --client claude

Paste the following into Settings → Cursor Settings → MCP → Add new server:

• Mac/Linux

npx -y @smithery/cli@latest run @JackKuo666/pubmed-mcp-server --client cursor --config "{}" 

npx -y @smithery/cli@latest install @JackKuo666/pubmed-mcp-server --client windsurf --config "{}"

npx -y @smithery/cli@latest install @JackKuo666/pubmed-mcp-server --client cline --config "{}"

1. Clone the repository:

   git clone https://github.com/JackKuo666/PubMed-MCP-Server.git
   cd PubMed-MCP-Server
   

2. Install the required dependencies:

   pip install -r requirements.txt
   

Start the MCP server:

python pubmed_server.py

Add this configuration to your claude_desktop_config.json:

(Mac OS)

{
  "mcpServers": {
    "pubmed": {
      "command": "python",
      "args": ["-m", "pubmed-mcp-server"]
      }
  }
}

(Windows version):

{
  "mcpServers": {
    "pubmed": {
      "command": "C:\\Users\\YOUR\\PATH\\miniconda3\\envs\\mcp_server\\python.exe",
      "args": [
        "D:\\code\\YOUR\\PATH\\PubMed-MCP-Server\\pubmed_server.py"
      ],
      "env": {},
      "disabled": false,
      "autoApprove": []
    }
  }
}

Using with Cline

{
  "mcpServers": {
    "pubmed": {
      "command": "bash",
      "args": [
        "-c",
        "source /home/YOUR/PATH/mcp-server-pubmed/.venv/bin/activate && python /home/YOUR/PATH/pubmed-mcp-server.py"
      ],
      "env": {},
      "disabled": false,
      "autoApprove": []
    }
  }
}

The PubMed MCP Server provides the following tools:

1. search_pubmed_key_words: Search for articles on PubMed using keywords.
2. search_pubmed_advanced: Perform an advanced search for articles on PubMed with multiple parameters.
3. get_pubmed_article_metadata: Fetch metadata for a PubMed article using its PMID.
4. download_pubmed_pdf: Attempt to download the full-text PDF for a PubMed article.
5. deep_paper_analysis: Perform a comprehensive analysis of a PubMed article.

You can ask the AI assistant to search for papers using queries like:

Can you search PubMed for recent papers about CRISPR?

Once you have a PMID, you can ask for more details:

Can you show me the metadata for the paper with PMID 12345678?

You can request a deep analysis of a paper:

Can you perform a deep analysis of the paper with PMID 12345678?

• pubmed_server.py: The main MCP server implementation using FastMCP
• pubmed_web_search.py: Contains the logic for searching PubMed and retrieving article information

• Python 3.10+
• FastMCP
• asyncio
• logging
• requests
• beautifulsoup4

Contributions are welcome! Please feel free to submit a Pull Request.

This project is licensed under the MIT License.

This tool is for research purposes only. Please respect PubMed's terms of service and use this tool responsibly.