mcp-server-pubtator3

mcp-server-pubtator3

3.3
research_and_data

If you are the rightful owner of mcp-server-pubtator3 and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.

This project provides an async Python server for interacting with the PubTator3 API, supporting tasks such as entity lookup, biomedical literature search, and text extraction from PubMed/PMC articles.

The Pubtator MCP Server is an asynchronous Python server designed to interface with the PubTator3 API, offering a suite of biomedical text-mining tools compatible with the Model Context Protocol (MCP). It facilitates tasks such as entity lookup, literature search, and text extraction from PubMed/PMC articles. The server is built using `aiohttp` for non-blocking HTTP requests, ensuring fast and efficient operations. It is particularly useful for integrating into broader MCP environments, providing programmatic access to biomedical concept lookup, literature search, full-text extraction, and entity relation discovery. The server supports multiple tools, each designed to handle specific tasks, making it a versatile solution for biomedical research and data analysis.

Features

  • Entity Autocomplete: Find biomedical entities (genes, diseases, chemicals, variants) using free-text queries.
  • Literature Search: Search the PubTator3 database using keywords, entity IDs, or entity relations.
  • Article Retrieval: Download and extract text from PubMed/PMC articles in multiple formats.
  • Find Related Entities: Query for entities related to a given identifier via customizable relation and type filters.
  • Async and Fast: Uses `aiohttp` for non-blocking HTTP requests; designed for integration into broader MCP environments.

Tools

  1. find_entity

    Find the identifier(s) for a specific bioconcept using a free text query.

  2. search_pubtator

    Search for relevant PubMed/PMC articles in PubTator3 using flexible queries.

  3. get_paper_text

    Download and extract the text content from a PubMed or PMC article.

  4. find_related_entities

    Find entities related to a specific PubTator entity, filtered by relation type or entity type.

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