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649,985 tools. Updated 2026-10-10 04:35

"PubMed" matching MCP tools:

  • Resolve a name or an identifier to an OpenAlex ID. ALWAYS use this before filtering by entity — names are ambiguous, IDs are not. A name returns up to 10 autocomplete matches with disambiguation hints. An identifier — OpenAlex ID, DOI, ORCID, ROR, PMID, or ISSN, bare or in URL form — resolves directly to the one record it addresses, and needs no entity_type. A PMCID is recognized as well, bare or as a PubMed Central URL, but OpenAlex indexes no PMCIDs, so it resolves nothing — pass the work's PMID or DOI instead.
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  • Export scholarly identifiers to a bibliography file format ready to write to disk or paste into a reference manager. Use when the user wants a file (.bib, .ris, .nbib, .xml, .rdf, .csv) for Zotero, Mendeley, EndNote, RefWorks, BibTeX/LaTeX, Pandoc, or Excel. Format parameter is required: bib (BibTeX — LaTeX), ris (RIS — most widely supported by reference managers), csl (CSL JSON — Pandoc/Quarto), endnote-xml, endnote-refer, refworks, medline (NBIB — PubMed round-trips, clinical workflows), zotero-rdf, csv (spreadsheet-friendly), or txt (plain-text bibliography rendered with the optional style parameter — txt is the only format that uses style; the others have their own structured shape and ignore it). Accepts the same identifier formats as resolveIdentifier (DOI/PMID/PMCID/ISBN/arXiv/ISSN/ADS/WHO IRIS, prefixes tolerated), single or comma/newline-separated batch — one round trip per call. Returns: { content: string, format: string } where content is the entire bibliography in the requested format as a single string — write it to a file (.bib/.ris/.nbib/etc.) or paste it directly into the target tool. Use formatCitation instead when the user wants in-line citation text (manuscript, slide); use resolveIdentifier when they want raw structured metadata. Read-only and idempotent — safe to retry. Works anonymously against the public Scholar Sidekick API (rate-limited free tier); set SCHOLAR_API_KEY (a free ssk_ key from https://scholar-sidekick.com/account) for higher limits, or RAPIDAPI_KEY for paid RapidAPI tiers. Rate limits follow your tier.
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  • Export scholarly identifiers to a bibliography file format ready to write to disk or paste into a reference manager. Use when the user wants a file (.bib, .ris, .nbib, .xml, .rdf, .csv) for Zotero, Mendeley, EndNote, RefWorks, BibTeX/LaTeX, Pandoc, or Excel. Format parameter is required: bib (BibTeX — LaTeX), ris (RIS — most widely supported by reference managers), csl (CSL JSON — Pandoc/Quarto), endnote-xml, endnote-refer, refworks, medline (NBIB — PubMed round-trips, clinical workflows), zotero-rdf, csv (spreadsheet-friendly), or txt (plain-text bibliography rendered with the optional style parameter — txt is the only format that uses style; the others have their own structured shape and ignore it). Accepts the same identifier formats as resolveIdentifier (DOI/PMID/PMCID/ISBN/arXiv/ISSN/ADS/WHO IRIS, prefixes tolerated), single or comma/newline-separated batch — one round trip per call. Returns: { content: string, format: string } where content is the entire bibliography in the requested format as a single string — write it to a file (.bib/.ris/.nbib/etc.) or paste it directly into the target tool. Use formatCitation instead when the user wants in-line citation text (manuscript, slide); use resolveIdentifier when they want raw structured metadata. Read-only and idempotent — safe to retry. Works anonymously against the public Scholar Sidekick API (rate-limited free tier); set SCHOLAR_API_KEY (a free ssk_ key from https://scholar-sidekick.com/account) for higher limits, or RAPIDAPI_KEY for paid RapidAPI tiers. Rate limits follow your tier.
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  • Map identifiers between databases. SYNTAX: biobtree_map(terms="ID", chain=">>source>>target") - Chain MUST start with ">>" - Source MUST match input ID type ID TYPE → SOURCE: - ENSG* → >>ensembl - P*/Q*/O* → >>uniprot - CHEMBL* → >>chembl_molecule - GO:* → >>go - MONDO:* → >>mondo - HP:* → >>hpo - HGNC:* or gene symbols → >>hgnc SOME DRUG EXPLORATION PATHS: - >>chembl_molecule>>chembl_target>>uniprot (drug targets) - >>pubchem>>pubchem_activity>>uniprot (bioactivity) - >>gtopdb_ligand>>gtopdb_interaction>>gtopdb>>uniprot (curated pharmacology with affinity data) - >>ensembl>>reactome>>chebi (pathway chemicals - when no direct targets) - Discover more via entry xrefs + EDGES WARNING - GO terms with high xref_count (>100): - Don't map GO → proteins → drugs (too many results) - Instead: search drug class for condition → verify targets this GO term DISEASE GENE PATTERNS: - >>mondo>>gencc>>hgnc (curated) - >>mondo>>clinvar>>hgnc (variant-based) - >>hgnc>>clingen_gene_validity (ClinGen evidence tier), >>hgnc>>clingen_dosage (haploinsufficiency), >>hgnc>>clingen_variant>>clinvar (ACMG, then dbsnp) CANCER / CELL LINE: - >>hgnc>>intogen (cancer driver gene?), >>hgnc>>civic (clinical variant interpretations) - >>uniprot>>cellosaurus (cell lines for a protein/gene) - >>hgnc>>depmap (CRISPR essentiality / target tractability), >>hgnc>>entrez>>depmap_dependency>>cellosaurus (which lines depend on the gene) GENE FUNCTION / LITERATURE: - >>entrez>>generif (cited one-line functional claims; >>generif>>pubmed for citations) DISEASE → DRUG PATTERNS: - >>mesh>>chembl_molecule (MeSH disease/condition → drugs with indications) - >>mondo>>clinical_trials>>chembl_molecule (disease → trial drugs) DISCOVERY APPROACH: - Use biobtree_entry to see xrefs (what's connected) - Use EDGES above to see where each dataset leads - Build chains based on what connections exist for YOUR entity RETURNS: mapped identifiers with dataset and name EDGES (what connects to what): ensembl: uniprot, go, transcript, exon, ortholog, paralog, hgnc, entrez, refseq, bgee, gwas, gencc, antibody, scxa, civic, intogen, hpa, hpa_antibody, pharmgkb_var_annotation, chembl_mechanism, ncrna_disease, ncrna_interaction, ncrna_drug, alliance_disease, gnomad_constraint, drugcentral, panelapp_gene hgnc: ensembl, uniprot, entrez, gencc, pharmgkb_gene, msigdb, clinvar, mim, refseq, alphafold, collectri, gwas, hpo, cellphonedb, civic, intogen, cellosaurus, clingen_gene_validity, clingen_dosage, clingen_variant, depmap, hpa, pharmgkb_var_annotation, chembl_mechanism, ncrna_disease, ncrna_interaction, ncrna_drug, alliance_disease, drugcentral, panelapp_gene, gnomad_constraint, mavedb entrez: ensembl, uniprot, refseq, go, biogrid, pubchem_activity, ctd_gene_interaction, dbsnp, civic, intogen, clingen_dosage, generif, depmap, depmap_dependency, hpa, pharmgkb_var_annotation, orthologentrez, relatedentrez, neighborentrez, mgi, rgd, zfin, wormbase, xenbase, sgd, flybase, gnomad_constraint, drugcentral orthologentrez: entrez # cross-species gene orthologs (NCBI gene_orthologs). >>entrez>>orthologentrez gives ortholog genes (filter species via taxonomy); reliable from model-organism genes (human-gene side currently incomplete) relatedentrez: entrez # related genes (bidirectional): NCBI gene_group (functional gene/pseudogene/readthrough/region) + HGNC gene-family co-members neighborentrez: entrez # genomic neighbors (left/right/overlapping); edge carries distance + side, neighbor strand/position in attrs; filter to genes via [type!="biological-region"] gnomad_constraint: ensembl, entrez, hgnc, transcript # gene LoF constraint (pLI/LOEUF/oe_lof); reach via >>ensembl>>gnomad_constraint drugcentral: chembl_molecule, pubchem, uniprot, ensembl, hgnc, entrez # approved drugs -> targets/MOA + FDA/EMA/PMDA approval; reach via name/INN/InChIKey or compound (chembl_molecule/pubchem >> drugcentral) refseq: ensembl, entrez, taxonomy, ccds, uniprot, mirdb mirdb: refseq transcript: ensembl, exon, ufeature, alphamissense, civic_variant, gnomad_constraint, mavedb uniprot: ensembl, alphafold, interpro, pfam, pdb, ufeature, intact, string, string_interaction, biogrid, biogrid_interaction, chembl_target, go, reactome, rhea, swisslipids, bindingdb, antibody, pubchem_activity, cellphonedb, jaspar, signor, diamond_similarity, esm2_similarity, alphamissense, cellosaurus, hpa, chembl_mechanism, ncrna_interaction, drugcentral, mavedb alphafold: uniprot interpro: uniprot, go, interproparent, interprochild chembl_molecule: mesh, chembl_activity, chembl_target, pubchem, chebi, clinical_trials, chembl_moleculeparent, chembl_moleculechild, chembl_mechanism, ncrna_drug, faers, drugcentral # parent=anhydrous/parent form, child=salt forms chembl_activity: chembl_molecule, chembl_assay, bao chembl_assay: chembl_activity, chembl_target, chembl_document, bao chembl_target: chembl_assay, uniprot, chembl_molecule, chembl_mechanism chembl_mechanism: chembl_molecule, chembl_target, uniprot, hgnc, ensembl # curated drug mechanism-of-action (incl. RNA therapeutics): drug >> chembl_mechanism, target/gene >> chembl_mechanism pubchem: chembl_molecule, chebi, hmdb, pubchem_activity, pubmed, patent_compound, bindingdb, ctd, pharmgkb, ncrna_drug, faers, drugcentral faers: chembl_molecule, pubchem, faers_reaction # openFDA FAERS drug->adverse-event; faers (per-drug master) -> faers_reaction children (PRR), reach via drug name or compound. NOTE co-occurrence not causation faers_reaction: faers # one per (drug,reaction): report_count, prr, serious_count, outcome; most-reported first pubchem_activity: pubchem, ensembl, uniprot chebi: pubchem, rhea, intact swisslipids: uniprot, go, chebi, uberon, cl lipidmaps: chebi, pubchem dbsnp: entrez, clinvar, pharmgkb_variant, alphamissense, spliceai, pharmgkb_var_annotation clinvar: hgnc, mondo, hpo, dbsnp, orphanet, civic_variant, cellosaurus, clingen_variant alphamissense: uniprot, transcript mavedb: uniprot, hgnc, ensembl, transcript # deep-mutational-scanning functional variant scores (ACMG PS3/BS3); reach via gene/protein >> mavedb; per-variant score + hgvs_pro + license # VARIANT-EFFECT SCORES — look up by the variant's OWN key with biobtree_entry(dataset=..), NOT via >>chains: # conservation key "chr:pos" (GRCh38) per-position phyloP / GERP / phastCons (also covers non-missense/splice positions) # gnomad_variant key "chr:pos:ref:alt" (GRCh38) gnomAD v4.1 genomes allele freq (af, grpmax, per-ancestry); also xrefs dbsnp # revel key "chr:pos:ref:alt" (GRCh38) REVEL ensemble missense pathogenicity (0-1, higher = pathogenic) # saprot key "uniprot:protein_variant" SaProt protein-LM variant effect (LLR <=0, lower = more damaging), e.g. P01116:G12D gwas: gwas_study, efo, dbsnp, hgnc, mondo gwas_study: gwas, efo, mondo mondo: gencc, clinvar, efo, mesh, hpo, clinical_trials, antibody, cellxgene, cellxgene_celltype, orphanet, mondoparent, mondochild, gwas, gwas_study, civic, intogen, cellosaurus, doid, mim, ncit, umls, medgen, gard, sctid, icd9, icd10cm, icd10who, icd11, nando, meddra, nord, uberon, ncrna_disease, panelapp_gene # disease cross-refs + disease_has_location anatomy, from the Mondo OBO doid: mondo, alliance_disease, doidparent, doidchild # Disease Ontology (now a full ontology w/ hierarchy); reach MONDO + its disease graph via the mondo<->doid bridge alliance_disease: hgnc, mgi, rgd, zfin, sgd, wormbase, flybase, xenbase, doid, pubmed # cross-species + human gene->disease (Alliance of Genome Resources); gene >> alliance_disease >> doid, or doid >> alliance_disease >> mgi/rgd/... for model-organism genes alliance_phenotype: mgi, rgd, wormbase, xenbase, mp, wbphenotype, xpo, pubmed # model-organism gene -> OBSERVED knockout/mutant phenotypes (distinct from the upheno ontology-translation path). Reach from the model-organism gene directly: mgi/rgd/wormbase/xenbase >> alliance_phenotype >> mp gencc: mondo, hpo, hgnc, ensembl clingen_gene_validity: hgnc, entrez, ensembl, mondo # ClinGen gene-disease validity tier (Definitive..Refuted) + MOI clingen_dosage: entrez, hgnc, ensembl, mondo, mim, pubmed # ClinGen haploinsufficiency/triplosensitivity per gene clingen_variant: clinvar, hgnc, entrez, ensembl, mondo, pubmed # ClinGen VCEP ACMG variant pathogenicity (clinvar bridges to dbsnp) panelapp: panelapp_gene # Genomics England clinical gene panels (per-panel master); panel >> panelapp_gene >> hgnc for the panel's genes panelapp_gene: panelapp, hgnc, ensembl, mim, mondo # one per (panel,gene), green/amber confidence + mode-of-inheritance; a gene's panels via >>hgnc (panelapp_gene) ; the panel's disease via mondo/mim clinical_trials: mondo, chembl_molecule pharmgkb: hgnc, dbsnp, mesh, pharmgkb_gene, pharmgkb_variant, pharmgkb_clinical, pharmgkb_guideline, pharmgkb_pathway pharmgkb_variant: pharmgkb_clinical, hgnc, mesh, dbsnp pharmgkb_gene: hgnc, entrez, ensembl, pharmgkb pharmgkb_clinical: dbsnp, hgnc, mesh, pharmgkb_variant, pharmgkb # pharmgkb = reverse drug→clinical edge (drug >> pharmgkb >> pharmgkb_clinical) pharmgkb_guideline: hgnc, pharmgkb pharmgkb_pathway: hgnc, pharmgkb pharmgkb_var_annotation: hgnc, entrez, ensembl, dbsnp, pubmed # per-publication variant-annotation evidence (finding sentence, PMID, significance, study stats) beneath pharmgkb_clinical; reach via gene or rsID ctd: mesh, ctd_gene_interaction, ctd_disease_association, pubchem ctd_gene_interaction: ctd, entrez, taxonomy, pubmed ctd_disease_association: ctd, mesh, mim, pubmed intact: uniprot, chebi, rnacentral string: uniprot, string_interaction string_interaction: string, uniprot biogrid: entrez, uniprot, refseq, taxonomy bgee: ensembl, uberon, cl, taxonomy, bgee_evidence bgee_evidence: bgee, uberon, cl cellxgene: cl, uberon, mondo, efo, taxonomy cellxgene_celltype: cl, uberon, mondo scxa: cl, uberon, taxonomy, ensembl, scxa_gene_experiment scxa_expression: ensembl, scxa, scxa_gene_experiment scxa_gene_experiment: ensembl, scxa, scxa_expression, cl hpa: ensembl, uniprot, hgnc, entrez, go, uberon, hpa_expression, hpa_pathology, hpa_antibody # Human Protein Atlas gene card: subcellular location (→go), specificity calls, top tissues hpa_expression: hpa, uberon, cellosaurus # per (gene,tissue/cell-line) RNA nTPM + IHC staining; reach genes-in-a-tissue via uberon >> hpa_expression hpa_pathology: hpa # per (gene,cancer) prognostic survival association hpa_antibody: hpa, ensembl # HPA validation antibody (reliability, antigen) rnacentral: uniprot, ensembl, intact, hgnc, refseq, ena, go # go = Rfam-projected GO annotations; rfam_id/rfam_description are attrs on the entry ncrna_disease: hgnc, ensembl, mondo, efo, pubmed # curated ncRNA->disease (LncRNADisease + HMDD); reach from the ncRNA gene ncrna_interaction: hgnc, ensembl, uniprot, pubmed # experimentally-supported ncRNA->protein interactions (NPInter) ncrna_drug: hgnc, ensembl, chembl_molecule, pubchem, pubmed # ncRNA drug-resistance / drug-target (ncRNADrug) reactome: ensembl, uniprot, chebi, go, reactomeparent, reactomechild rhea: chebi, uniprot, go go: ensembl, uniprot, reactome, msigdb, swisslipids, bgee, interpro, goparent, gochild, hpa, rnacentral hpo: clinvar, gencc, mondo, msigdb, orphanet, mim, hmdb, hgnc, hpoparent, hpochild, upheno efo: gwas, mondo, cellxgene, efoparent, efochild, ncrna_disease upheno: hpo, mp, zp, xpo, wbphenotype, fypo, uphenoparent, uphenochild # cross-species phenotype hub. A GENE's model-organism phenotypes are reached THROUGH hpo (genes are NOT linked directly to mp/upheno): >>hgnc>>hpo>>upheno>>mp (mouse), >>hgnc>>hpo>>upheno>>zp (zebrafish), ...>>xpo/wbphenotype/fypo. So gene->human HP phenotypes -> their cross-species equivalents. mp: upheno, mpparent, mpchild, alliance_phenotype # Mammalian Phenotype Ontology (mouse/rat). Reach from a gene via >>hgnc>>hpo>>upheno>>mp (NOT >>hgnc>>mp); observed model phenotypes via alliance_phenotype. zp: upheno, zpparent, zpchild # Zebrafish Phenotype Ontology. Reach from a gene via >>hgnc>>hpo>>upheno>>zp. xpo: upheno, xpoparent, xpochild, alliance_phenotype # Xenopus Phenotype Ontology wbphenotype: upheno, wbphenotypeparent, wbphenotypechild, alliance_phenotype # C. elegans Phenotype Ontology fypo: upheno, fypoparent, fypochild # Fission Yeast Phenotype Ontology uberon: bgee, cellxgene, cellxgene_celltype, swisslipids, uberonparent, uberonchild, hpa, hpa_expression cl: bgee, cellxgene, cellxgene_celltype, scxa, scxa_gene_experiment, clparent, clchild taxonomy: ensembl, uniprot, bgee, biogrid, ctd_gene_interaction, taxparent, taxchild mesh: pharmgkb, ctd, ctd_disease_association, pubchem, mondo, chembl_molecule, meshparent, meshchild eco: ecoparent, ecochild antibody: ensembl, uniprot, mondo, pdb msigdb: hgnc, entrez, go, hpo orphanet: hpo, uniprot, mondo, hgnc, clinvar, mim, mesh mim: clinvar, hpo, mondo, uniprot, ctd_disease_association, panelapp_gene hmdb: pubchem, hpo, chebi, uniprot collectri: hgnc # transcription factor → target gene interactions esm2_similarity: uniprot # protein structural similarity diamond_similarity: uniprot # protein sequence similarity cellphonedb: uniprot, ensembl, hgnc, pubmed # ligand-receptor pairs for cell-cell communication spliceai: hgnc pdb: uniprot, go, interpro, pfam, taxonomy, pubmed fantom5_promoter: ensembl, hgnc, entrez, uniprot, uberon, cl fantom5_enhancer: ensembl, uberon, cl fantom5_gene: ensembl, hgnc, entrez jaspar: uniprot, pubmed, taxonomy encode_ccre: taxonomy bao: chembl_activity, chembl_assay, baoparent, baochild brenda: uniprot, pubmed, brenda_kinetics, brenda_inhibitor brenda_kinetics: brenda brenda_inhibitor: brenda gtopdb: uniprot, hgnc, gtopdb_ligand, gtopdb_interaction # drug targets (GPCRs, ion channels, enzymes) gtopdb_ligand: pubchem, chebi, chembl_molecule, gtopdb_interaction # ligands/drugs with binding data gtopdb_interaction: gtopdb, gtopdb_ligand, pubmed # target-ligand binding with affinity values civic: entrez, ensembl, civic_variant, civic_evidence, civic_assertion # clinical interpretation of cancer variants civic_variant: civic, clinvar, civic_evidence, civic_assertion, transcript civic_evidence: civic_variant, civic, mondo, chembl_molecule, pubmed, clinical_trials civic_assertion: civic_variant, civic, mondo, chembl_molecule intogen: hgnc, entrez, ensembl, mondo, pubmed # cancer driver genes cellosaurus: taxonomy, uniprot, hgnc, mondo, orphanet, clinvar, dbsnp, uberon, cl, chebi, doi, patent, pubmed, depmap_dependency, hpa_expression # cell lines (CVCL) generif: entrez, pubmed # NCBI cited per-gene functional claims (RAG grounding) depmap: entrez, hgnc, ensembl # CRISPR gene essentiality aggregate (cancer dependency / target tractability) depmap_dependency: entrez, cellosaurus # per cell-line gene dependency (effect < -0.5) FILTER SYNTAX: >>dataset[field operator value] OPERATORS: == equals >>dataset[field=="value"] != not equals >>dataset[field!="value"] > greater than >>dataset[field>value] < less than >>dataset[field<value] >= greater or equal >>dataset[field>=value] <= less or equal >>dataset[field<=value] contains string match >>dataset[field.contains("value")] LOGICAL OPERATORS: && AND >>dataset[field1>5 && field2<10] || OR >>dataset[field=="A" || field=="B"] ! NOT >>dataset[!field] or >>dataset[!(field=="value")] TYPE RULES: - FLOAT: use decimal point (70.0 not 70) - INT: no decimal (2 not 2.0) - STRING: quote values ("Pathogenic", "PHASE3") - BOOL: true/false (no quotes) EXAMPLES: >>chembl_molecule[highestDevelopmentPhase==4] # approved drugs >>chembl_molecule[highestDevelopmentPhase>=3] # Phase 3+ >>clinical_trials[phase=="PHASE3"] >>go[type=="biological_process"] >>clinvar[germline_classification=="Pathogenic"] >>reactome[name.contains("signaling")] >>gtopdb[type=="gpcr"] # GPCR targets >>gtopdb[type=="ion_channel"] # ion channel targets >>gtopdb_ligand[approved==true] # approved drugs only >>gtopdb_interaction[endogenous==true] # endogenous ligand interactions
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  • Retrieve works associated with an ORCID iD — publications, datasets, software, preprints, and more. Returns work summaries with put-codes, titles, types, publication dates, journal names, and all external identifiers (DOIs, PMIDs, arXiv IDs, ISBNs). The first 50 works are returned by default; workCount reports the total available, and prolific records are paged with offset and the returned nextOffset (or raise limit). A page also stops early once the response reaches its 64,000-byte budget, so returnedCount can come in below limit; truncated and nextOffset then carry the continuation. Set include_external_ids to false to omit identifier lists for a lighter payload. Pass the putCode from each work to orcid_get_work_detail to retrieve the full record including abstract and contributors. External IDs are ready for chaining to Crossref, PubMed, or arXiv servers. Works come from the researcher or from member organizations such as Crossref or a university system; each work lists its sources and whether the researcher asserted it (selfAsserted). A researcher may not have linked all their publications.
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Matching MCP Servers

  • A
    license
    A
    quality
    B
    maintenance
    Enables biomedical literature research with 17 tools for searching and retrieving publications, full texts, MeSH terms, citations, clinical trials, drug safety data, and more from multiple sources without requiring API keys.
    17
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    Analyzes PubMed medical literature to help researchers quickly gain insights into medical research dynamics, with features including literature retrieval, hotspot analysis, trend tracking, and comprehensive reports.
    149
    MIT

Matching MCP Connectors

  • PubMed MCP — wraps the NCBI E-utilities API (biomedical literature, free, no auth)

  • Search PubMed and summarize biomedical literature — designed for AI health agents.

  • Look up a Wikidata entity by an external identifier such as a DOI, PubMed ID, ORCID iD, or OpenAlex ID. Returns match=<entity> on success, match=null when not found, and match=null with multipleMatches populated when a Wikidata data integrity issue causes more than one entity to claim the same external ID. Common cross-server join use cases: CrossRef DOI → Wikidata paper QID (P356), PubMed PMID → Wikidata paper QID (P698), ORCID → author QID (P496), OpenAlex ID → entity QID (P10283). The property must be one whose Wikidata data type is external-id — item-valued or media properties (e.g. P31 instance-of, P18 image) are rejected rather than returning an empty match. Known value normalization is applied automatically: surrounding whitespace is trimmed, identifier-resolver URL prefixes are stripped (https://doi.org/, https://pubmed.ncbi.nlm.nih.gov/, https://orcid.org/), DOIs are uppercased, PMID prefixes stripped, ORCID hyphens normalized.
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  • Predict the functional consequences of a sequence variant using the Ensembl Variant Effect Predictor (VEP). Accepts three input formats: HGVS notation (transcript-relative, e.g. ENST00000380152.8:c.2T>A, or genomic, e.g. 13:g.32316462T>A); region+allele (chr:start:end:strand/allele, e.g. 1:65568:65568:1/T); and a dbSNP rsID (e.g. rs334). Returns the most severe consequence term, affected transcripts and genes, impact level (HIGH/MODERATE/LOW/MODIFIER), and any colocated known variants with clinical significance. HGVS input: provide the full notation including transcript version for best results. Region+allele input: Ensembl normalizes chromosome names and canonical vertebrate output omits the chr prefix (a chr-prefixed name is also accepted). By default the response caps transcript consequences (max_transcript_consequences) and per-variant PubMed IDs (max_pubmed_ids_per_variant) to keep large VEP results compact — well-studied variants like rs334 otherwise carry 60+ consequences and 100+ citations. Truthful totals are always reported; set a cap to 0 (or include_all_colocated_pubmed=true) to retrieve the full set.
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  • Verify a pasted reference list (plain text, BibTeX or RIS) against Crossref, OpenAlex, DataCite, Semantic Scholar, arXiv, PubMed and DBLP, plus Retraction Watch. Flags references that cannot be found (possibly fabricated), retracted papers and DOI mismatches. One check per day without an account; sign in for more.
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  • Find cancer cell lines by name, ranked by mutation burden. Returns each matching cell line with its tissue of origin, cancer type, total mutations, unique mutant peptides, data sources (COSMIC / DepMap-CCLE / PubMed), and Cellosaurus ID. Covers only cell-line models (kept separate from primary tissue samples). Use before `get_cell_line` or `top_genes_in_cell_line`. Ordered by mutation count (most mutated first).
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  • Get the full abstract and metadata of an MMWR article by PubMed ID. Returns the complete abstract, authors, publication date, volume/issue, and any MeSH subject headings. Use PMIDs from search_mmwr or get_recent_reports results. Args: pmid: PubMed ID of the MMWR article (e.g. '38271059').
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  • Search Cochrane systematic reviews via PubMed. Finds Cochrane Database of Systematic Reviews articles matching your query. Returns PubMed IDs, titles, and publication dates. Use get_review_detail with a PMID to get the full abstract. Args: query: Search terms for finding reviews (e.g. 'diabetes exercise', 'hypertension treatment', 'childhood vaccination safety'). limit: Maximum number of results to return (default 20, max 100).
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  • Get full details of a Cochrane systematic review by PubMed ID. Returns the complete abstract, authors, publication info, MeSH terms, and conclusions of a Cochrane review. Use PMIDs from search_reviews results. Args: pmid: PubMed ID of the review (e.g. '35658166').
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  • Search Europe PMC, a broad open-access biomedical corpus. Surfaces preprints (`source: PPR`), patents (`source: PAT`), Agricola (`source: AGR`), plus everything in PubMed (`MED`) and PMC. Use when additional coverage is needed — preprints and EPMC-only OA records are the typical recovery. Paginate via `cursorMark`. Defaults to `MED`, `PMC`, and `PPR`; pass `sources` to include `PAT` / `AGR`. Abstracts arrive as a bounded `abstractSnippet` with `abstractTruncated` marking the cut ones — pass a hit’s `source` and `epmcId` to `pubmed_europepmc_fetch` for the complete abstract.
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  • Search PubMed (NCBI) for medical / life-sciences literature by keyword. Returns enriched article list: pmid, title, authors, journal, year, pub_types, plus a year-range + has-meta-analysis / has-review enrichment block. Ideal for medical RAG agents. Priced at $0.005 USDC on Base (x402). Pass a signed x402 v2 authorization as the '_payment' argument to unlock the paid response. Without it, the tool returns the 402 accept-list for your wallet to sign.
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  • ✅ No API key needed — call this now. Navigator for the full A2AWire tool surface. Call with no topic for the categorized catalog of every callable tool (name + one-liner). Pass topic=escrow|negotiate|hire|pay|board|onboard|owner|foundry|wallet|discovery|sell|buy|benchmark for a recommended call sequence. Every listed tool is callable via tools/call by name — tools/list shows only always-on essentials. Optional 30-second tour: curl -sSL https://a2awire.com/api/v1/scripts/quickstart.sh | sh — see the economy live and your path to earning.
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  • Live search of PubMed, Europe PMC and clinical guidelines. Returns up to eight sources for a clinical or research question, each with its study type, evidence level and link, usually in about 20 seconds. It does not write an answer: cite the sources by number, or use ask_cliniatlas for a full cited answer. For an EU medicine's label or SmPC, use lookup_eu_medicine. Do not include patient identifiers. Searches are limited per user per day.
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  • Search clinical trials related to a health condition via PubMed. Finds clinical trial publications matching the condition and optional intervention. Returns trial titles, authors, and PubMed IDs. Args: condition: The health condition or disease (e.g. 'type 2 diabetes', 'breast cancer', 'depression'). intervention: Optional treatment or intervention to include in search (e.g. 'metformin', 'cognitive behavioral therapy'). limit: Maximum number of results to return (default 20, max 100).
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  • Spell-check a PubMed search query against NCBI ESpell and get the corrected query back. Use after a zero-hit or thin `pubmed_search_articles` result, or when a drug, gene, disease, or author name may be misspelled — every misspelled token is corrected in one call (`alzhiemer diseese treatmnt outcomse` → `alzheimer disease treatment outcomes`), and `hasSuggestion` is false when NCBI has no change to offer. Re-run the search with `corrected`.
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  • Convert between article identifiers (DOI, PMID, PMCID). Accepts up to 50 IDs of a single type per request. Only resolves articles indexed in PubMed Central — for articles not in PMC, use pubmed_search_articles instead.
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  • Get the headline size of the CAN-IMMUNE database in one call. Returns total counts of mutations, genes, and unique mutant peptides, plus how many cell lines, tissues, and cancer types are covered, and the data sources (COSMIC, DepMap/CCLE, PubMed). Use this first to size the resource or to answer "how big is the database / how many X are there" questions. No parameters.
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