The PubMed Enhanced Search MCP Server provides AI assistants with powerful tools to search and analyze academic medical literature through the PubMed database. It offers specialized functions for keyword searches with journal filtering, MeSH term lookups, publication count statistics, detailed paper information retrieval, and structured PICO-based evidence searches. Built with Python using the FastMCP framework, this server implements automatic retry mechanisms with backoff delays to handle potential rate limiting by NCBI's E-utilities service, making it particularly valuable for researchers, healthcare professionals, and academics who need to efficiently access and analyze medical research without leaving their AI assistant conversation.
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Highlight AISearch PubMed for articles matching keywords with optional journal filtering. Parameters: keywords (array of strings), journal (optional string), num_results (integer), sort_by (optional string)
Look up MeSH terms related to a medical concept. Parameters: concept (string)
Get the count of publications for multiple search terms. Parameters: terms (array of strings)
Get detailed information about specific papers by PMID. Parameters: pmids (array of strings)
Perform structured PICO (Population, Intervention, Comparison, Outcome) searches with synonyms. Parameters: p_terms (array of strings), i_terms (array of strings), c_terms (array of strings), o_terms (array of strings)
