PubTator MCP Server

Name: PubTator MCP Server
Author: BioMCP-Hub

@BioMCP-Hub

リポジトリ

PubTator MCP Server について

概要はまだありません

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基本情報

カテゴリ

その他

ライセンス

MIT

ランタイム

python

トランスポート

stdio

公開者

BioMCP-Hub

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

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 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