PubTator MCP Server

Name: PubTator MCP Server
Author: BioMCP-Hub

@BioMCP-Hub

代码仓库

关于 PubTator MCP Server

暂无概览

#mathgpt #math-solver #math-assistant

基本信息

分类

其他

许可证

MIT

运行时

python

传输方式

stdio

发布者

BioMCP-Hub

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "PubTator-MCP-Server": {
      "command": "npx",
      "args": [
        "-y",
        "@smithery/cli@latest",
        "install",
        "@JackKuo666/pubtator-mcp-server",
        "--client",
        "claude",
        "--config",
        "{}"
      ]
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is PubTator MCP Server?

It is a biomedical literature annotation and relationship mining server based on PubTator3, providing AI assistants access to PubTator3 through the Model Context Protocol (MCP). It allows AI models to programmatically search scientific literature, obtain annotation information, and analyze entity relationships.

How to use PubTator MCP Server?

Install via Smithery (npx command) or manually clone the repo and run pip install -r requirements.txt. Start the server with python pubtator_server.py. Configure transports via environment variables MCP_TRANSPORT, MCP_HOST, MCP_PORT. Use the MCP client (e.g., Claude Desktop, Cursor) to connect and call tools like export_publications, find_entity_id, find_related_entities, search_pubtator, and batch_export_from_search.

Key features of PubTator MCP Server

Export PubTator annotations in multiple formats (pubtator, biocxml, biocjson)
Look up standard identifiers for biological concepts via free text
Discover biomedical relationships (treat, cause, interact, etc.)
Search literature by keywords and entity IDs
Batch export annotations from search results

Use cases of PubTator MCP Server

Retrieve annotated publications for given PMIDs for analysis
Find the official ID of a gene, disease, or chemical from a natural language query
Identify entities related to a known biomedical concept
Search literature on a topic and export all annotations in batch
Integrate literature mining directly into AI assistant workflows