Pubmed Smithery
Enhance PubMed searches with features such as MeSH term lookup, publication count statistics, and PICO-based evidence search.
About
PubMed Smithery is a Model Content Protocol (MCP) server designed to enhance the process of searching and retrieving academic papers from the PubMed database. It extends beyond basic keyword searches, offering functionalities like MeSH (Medical Subject Headings) term lookup to refine search terms, publication count statistics for comparing the prevalence of different concepts, and structured PICO (Population, Intervention, Comparison, Outcome) based evidence search to aid in evidence-based literature reviews. By providing these features, PubMed Smithery streamlines research workflows and improves the efficiency of finding relevant scientific literature.
Key Features
- Search PubMed with keyword and journal filtering.
- Retrieve MeSH terms related to search words.
- Obtain publication counts for multiple search terms.
- Perform structured PICO-based searches with synonym support.
- Retrieve detailed paper information (abstract, DOI, authors, keywords).
- 2 GitHub stars
Use Cases
- Conducting evidence-based literature reviews using PICO framework.
- Comparing the prevalence of different medical concepts based on publication counts.
- Refining PubMed search queries using related MeSH terms.