PubTator MCP Server

@BioMCP-Hub

代码仓库

基本信息

分类

其他

许可证

MIT

传输方式

stdio

作者

BioMCP-Hub

关于 PubTator MCP Server

暂无概览

#mathgpt #math-solver #math-assistant

PubTator MCP Server 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",
        "{}"
      ]
    }
  }
}

PubTator MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。

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

常见问题

What are the rate limits?

API requests are limited to a maximum of 3 requests per second.

What data formats are supported for annotation export?

Supported formats are pubtator, biocxml, and biocjson.

What transport options are available?

The server supports both stdio and TCP transport, configurable via the `MCP_TRANSPORT` environment variable (default is TCP).

Are there any special requirements for entity IDs in relationship queries?

Entity IDs must start with "@", for example `@DISEASE_COVID-19`.

What are the runtime dependencies?

Python 3.10+ and the FastMCP library are required.

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