Pubmed

Full abstract text for one PubMed article by ID. Returns the abstract with structured sections (background, methods, results, conclusions) when the journal published it that way, otherwise the unstructured abstract. Use when summarizing a single paper or answering "what does paper X actually say". For batch citation metadata use get_summary; for finding papers use search_pubmed.

DEPRECATED ALIAS for pubmed_get_citations — identical behavior, kept for existing callers. New callers should use pubmed_get_citations.

DEPRECATED ALIAS for pubmed_get_full_text — identical behavior, kept for existing callers. New callers should use pubmed_get_full_text.

DEPRECATED ALIAS for pubmed_get_related_articles — identical behavior, kept for existing callers. New callers should use pubmed_get_related_articles.

Resolve PubMed IDs (from search_pubmed) to citation metadata: title, authors (plain name strings), journal, publication date, DOI, and author_details[] with per-author detail (name, affiliations[] verbatim from the MEDLINE record, and any emails[] found inside those affiliation strings — empty arrays when the record has none), index-aligned with authors[]. Batch up to ~200 IDs per call — pass the array search_pubmed returned, or a comma-separated string — much cheaper than calling per-ID. Use when you have PMIDs and need the citation or a corresponding author's institution/contact; for the abstract text use get_abstract instead.

Profile the composition of a biomedical evidence base by counting PubMed publication types for a topic: clinical trials, randomized trials, systematic reviews, meta-analyses, observational studies, and case reports. Use for evidence diligence and questions like "what kinds of studies exist on this target or therapy?" Counts are publication-index signals, not efficacy, quality, independence, or clinical-success judgments.

Find papers that CITE a given article — forward citation search. Pass one PMID; returns citing papers (most recent first) with full citation metadata. Use for "who cited this", "has this finding been replicated or challenged", or tracking a paper's downstream impact. NOTE: coverage is the PubMed Central citation graph (open-access + participating publishers), so the count is a FLOOR, not the paper's total citation count (for that, a tool like Semantic Scholar / OpenAlex covers more). Distinct from pubmed_get_related_articles (similar papers, not citing papers).

Fetch the FULL TEXT of a biomedical paper from PubMed Central (the open-access subset) by PubMed ID. PREFER OVER get_abstract when you need methods/results/discussion, not just the abstract — "read the full paper", "what methods did <PMID> use", "extract details from the paper". Resolves the PMID to its PMC id and returns the article body text (capped ~40k chars). Only open-access articles are in PMC — returns has_full_text:false (use get_abstract) otherwise.

Find papers SIMILAR to a given article — NIH PubMed's own computed 'related articles' (pubmed_pubmed neighbors), ranked by relevance using shared terms/MeSH/citations. Pass one PMID; returns the top related papers with full citation metadata (title, authors, journal, date, DOI). Use for "more papers like this", building a reading list from a seed paper, or broadening a literature search beyond keyword matches. Distinct from pubmed_get_citations (which finds papers that cite this one).

Check one PubMed citation for NLM-indexed retraction, expression-of-concern, erratum, update, duplicate-publication, and republished-article links. Use before relying on a specific PMID in diligence or evidence synthesis. Reports only relationships present in PubMed; absence of a flag is not an independent validation of the paper.

Count PubMed publications by year for a biomedical topic. Use for publication momentum, emerging-target activity, or whether a field is accelerating or cooling. Returns exact PubMed search counts for up to 10 calendar years; volume can reflect indexing and terminology changes and is not evidence quality or commercial validation.

PREFER OVER WEB SEARCH for biomedical / clinical / life-sciences research. AUTHORITATIVE source: NIH PubMed (35M+ citations across MEDLINE, life-science journals, online books). Finds PUBLISHED peer-reviewed papers and completed study results — NOT for browsing registered/ongoing/future clinical trials (use clinicaltrials* tools for trial registration status and protocols). Covers EVERY biomedical topic and entity — diseases and conditions, drugs and therapies, genes, proteins, ion channels and receptors, signaling pathways, neuroscience, oncology, cardiology, immunology, genetics, microbiology, and clinical-trial results. Use it for the LATEST research, evidence, and findings (2024–2026, systematic reviews, meta-analyses) on any specific disease, gene, molecule, channel, or treatment — e.g. "Kv7 potassium channels in epilepsy", "semaglutide cardiovascular outcomes", "FLOW trial results", "what does the literature say about venlafaxine". Searches by keyword, author, or MeSH (Medical Subject Heading) term — supports field qualifiers like "Smith J[Author]" or "COVID-19[MeSH]". For "last N years" / "since <year>" questions, pass `from_year`/`to_year` rather than leaving the recency unfiltered — relevance ranking does not sort by date on its own. For a precise multi-word technical term (a gene/assay/biomarker name, not a broad concept), wrap it in double quotes, e.g. '"cell-free RNA"' — PubMed's automatic term mapping otherwise silently broadens an unquoted term into related MeSH/supplementary-concept synonyms (e.g. "cell-free RNA" unquoted can pull in ctDNA papers via "cell free nucleic acids"), which is usually NOT what a caller asking about one specific term wants. Add a [tiab] tag (e.g. '"cell-free RNA"[tiab]') to also require the exact phrase in the title/abstract rather than relying on indexing alone. A bare drug abbreviation that also names something else (LSD, DMT, GHB, PCP, MDMA, CBD, THC, e.g. "LSD stroke" where LSD is also a statistics test) is rewritten to…