biomcp

name	biomcp
description	Search and retrieve biomedical data - genes, variants, clinical trials, diagnostic tests, articles, drugs, diseases, pathways, proteins, adverse events, pharmacogenomics, and phenotype-disease matching. Use for gene function, variant pathogenicity, trials, diagnostics, drug safety, pathway context, disease workups, and literature evidence.

BioMCP CLI

If you don't know how to start, run biomcp suggest "<question>" first, then open the returned biomcp skill <slug> playbook for the full workflow.

Routing rules

• Start with the narrowest command that matches the question.
• Use biomcp discover "<free text>" when you only have a single biomedical phrase and need the CLI to resolve the first typed command. discover is a single-entity resolver and single-entity free-text lookup only: use it to resolve the canonical name, ID, or category of one thing. It is not a relational query tool and not a list-question seed. Examples: biomcp discover BRCA1 and biomcp discover dabigatran. Symptom-of-disease prompts, HPO symptom bridges, treatment prompts, gene+disease orientation, and unambiguous gene-plus-topic follow-ups remain supported exceptions.
• Relational or multi-entity questions may redirect to biomcp search all --keyword "<query>" instead of surfacing weak collocation matches as if they were a resolved discover answer.
• Use biomcp search all --gene <gene> --disease "<disease>" when you know the entities but not the next pivot.
• Treatment questions: biomcp search drug --indication "<disease>" --limit 5
• Diagnostic-test questions: use structured pivots first with biomcp get gene <symbol> diagnostics or biomcp get disease "<disease>" diagnostics; use biomcp list diagnostic for the full source/filter/section contract; use biomcp search diagnostic --gene <symbol> --limit 5, biomcp search diagnostic --disease "<disease>" --source all --limit 5, or biomcp get diagnostic <id> when you need the full search/detail surface.
• Symptom or phenotype questions: biomcp get disease <name_or_id> phenotypes
• Gene-function questions: biomcp get gene <symbol>
• Drug-safety questions: biomcp drug adverse-events <name> and biomcp get drug <name> safety
• Drug-interaction questions: biomcp drug interactions <name> and biomcp get drug <name> interactions
• EMA and WHO regional drug data are local runtime files that auto-download on first use, DDInter is the local drug-interaction bundle, CDC CVX/MVX is the companion local vaccine-brand bridge for default/EU vaccine searches plus explicit WHO vaccine search, and GTR plus WHO IVD are local diagnostic-test backbones; run biomcp ddinter sync, biomcp ema sync, biomcp who sync, biomcp cvx sync, biomcp gtr sync, or biomcp who-ivd sync to force-refresh before freshness-sensitive local-runtime lookups.
• Vaccine brand-name questions that miss on MyChem often need biomcp search drug <brand> --region eu, omitted --region, or explicit biomcp search drug <brand> --region who --product-type vaccine, which can bridge through CDC CVX/MVX into EMA or WHO vaccine matches.
• Review-literature questions: biomcp search article -k "<query>" --type review --limit 5
• Keyword-only article searches may return _meta.suggestions[] objects when the whole keyword exactly matches a gene, drug, or disease label/alias; use the suggested get gene, get drug, or get disease command when structured data may answer before more article paging.
• For repeated article keyword searches in one task, use JSON plus --session <token> with a short non-secret local label. If the next keyword overlaps the previous same-session keyword, _meta.suggestions[] can point to prior article batch, discover, or date narrowing instead of more reformulation.
• Some first-call JSON responses include _meta.workflow and _meta.ladder[]; these are static sidecar-backed multi-step ladders. Treat _meta.next_commands as dynamic one-hop follow-ups and _meta.ladder[] as the worked-example path for the named workflow.
• After search article, default to biomcp article batch <id1> <id2> ... instead of repeated get article calls. Batch up to 20 shortlisted papers in one call.
• Use biomcp batch gene <GENE1,GENE2,...> when you need the same basic card fields, chromosome, or sectioned output for multiple genes.
• For diseases with weak ontology-name coverage, run biomcp discover "<disease>" first, then pass a resolved MESH:..., OMIM:..., ICD10CM:..., MONDO:..., or DOID:... identifier to biomcp get disease.
• Multi-hop article follow-up: biomcp article citations <id> --limit 5 and biomcp article recommendations <id> --limit 5

Section reference

• get gene ... protein: UniProt function and localization detail
• get gene ... hpa: Human Protein Atlas tissue expression and localization
• get gene ... expression: GTEx tissue expression
• get gene ... diseases: disease associations
• get gene ... diagnostics: GTR diagnostic-test pivot for a gene
• get article ... annotations: PubTator normalized entity mentions for standardized extraction
• get article ... tldr: Semantic Scholar summary and influence
• get disease ... genes: associated genes
• get disease ... phenotypes: HPO phenotype annotations; source-backed and sometimes incomplete
• get disease ... pathways: pathways from associated genes
• get disease ... diagnostics: GTR and WHO IVD diagnostic-test pivot for a condition
• get diagnostic ... genes: joined gene names from the GTR detail bundle
• get diagnostic ... conditions: joined disease or condition names from GTR
• get diagnostic ... methods: source-native GTR testing methods
• get diagnostic ... regulatory: opt-in FDA device 510(k) and PMA overlay for supported diagnostic records
• get drug ... label: FDA label indications, warnings, and dosage
• get drug ... regulatory: regulatory summary
• get drug ... safety: safety context and warnings
• get drug ... interactions: DDInter-backed structured drug-drug interactions plus source-scoped empty wording
• get drug ... targets: ChEMBL and OpenTargets targets
• get drug ... indications: OpenTargets indication evidence

Cross-entity pivot rules

• gene articles <symbol> and search article -g <symbol> are equivalent starting points for gene-filtered literature.
• Use helpers when the pivot is obvious: drug interactions, drug trials, disease trials, variant articles, article citations.
• Use sectioned diagnostic pivots for gene or disease contexts: get gene <symbol> diagnostics and get disease <name_or_id> diagnostics. Use biomcp list diagnostic for source/filter/section details, and inspect returned IDs with get diagnostic <id> rather than inventing accessions or product codes.
• Use search article -d "<disease>" --type review --limit 5 when disease phenotypes or drug indications look sparse.
• Use article batch as the default multi-article follow-up after search article; it replaces sequential get article calls and preserves Semantic Scholar enrichment when available.
• Use batch <entity> <id1,id2,...> --sections <s1,s2,...> when you need the same card shape for several entities.
• Use enrich <GENE1,GENE2,...> once you have a real gene set and want pathways or GO-style categories.

How-to reference

For question patterns that need more than a one-line routing hint, start with the executable command or routing phrase below before you improvise the command sequence.

Question pattern	Start with	Why
Specific variant pathogenicity or clinical-evidence question	biomcp get variant "<variant>"	Use the bounded variant-pathogenicity workflow instead of mixing ad hoc variant, trial, and article commands
Specific drug safety or adverse-event question	biomcp drug adverse-events <name> and biomcp get drug <name> safety	Start with the drug-safety workflow before widening to literature
Drug interaction question for a known medication	biomcp drug interactions <name> or biomcp get drug <name> interactions	Start with the DDInter-backed helper when the anchor drug is known, then widen to safety or literature only for nuance
Drug approval, licensing, or regulatory-date question	biomcp get drug <name> regulatory	Use the structured-first workflow discipline: check get drug ... regulatory before falling back to articles for approval facts
Broad gene-in-disease orientation	biomcp search all --gene <gene> --disease "<disease>"	Follow the shipped counts-first workflow for gene, drug, trial, and article pivots
Gene-disease association for a known gene	biomcp get gene <symbol> diseases	Check get gene ... diseases and search variant --gene ... for the full disease spectrum before searching articles
Gene localization or protein-function question	biomcp get gene <symbol> protein and biomcp get gene <symbol> hpa	Pull get gene ... protein and get gene ... hpa first because UniProt and HPA usually answer localization or function directly
Diagnostic-test inventory or detail question	biomcp list diagnostic and biomcp get diagnostic GTR000006692.3	Inspect the shipped diagnostic filters and sections first; use gene/disease diagnostic pivots or search diagnostic to get source-native IDs before get diagnostic detail
You know the concept but not the first entity to inspect	biomcp search all --keyword "<concept>"	Use search all to choose the next typed command intentionally
"Most common" or prevalence question about a disease	biomcp discover "<disease>"	Use biomcp discover to resolve the canonical disease entity, then inspect structured disease data before widening to article search
You already know the anchor entity and want the built-in related view	Use the matching helper such as biomcp gene articles <symbol>, biomcp drug interactions <name>, biomcp drug trials <name>, or biomcp disease trials "<disease>"	Move from a known gene, disease, drug, or variant into trials, articles, drugs, pathways, or interaction review without rebuilding the query
You need literature for a known gene, disease, drug, method, or outcome	biomcp search article -k "<query>" --type review --limit 5	Translate the question into typed flags plus a focused keyword clause
You need recruiting or completed trials for a disease, drug, or biomarker	biomcp search trial -c "<condition>" --limit 5	Start with condition and intervention filters, then add biomarker or geography only when needed
You need to resolve or annotate a variant identifier	biomcp get variant "<variant>"	Normalize the variant first, then add significance or frequency filters
You need a functional-effect prediction for a variant	biomcp get variant "<variant>" predict	Use predict only after you have a resolvable variant identifier
You need to reproduce a paper-style workflow	Map the paper task to the closest BioMCP entity command, then use biomcp article batch <pmid1> <pmid2> ... for shortlisted papers	Map the paper task to the closest BioMCP workflow area before copying commands
You need to review whether a workflow run is complete and trustworthy	Check command fidelity, evidence traceability, and reproducibility against the commands already run	Check command fidelity, evidence traceability, and reproducibility before signing off

Anti-patterns

Don't use discover for relational or list questions

discover resolves one biomedical entity at a time. If the prompt asks for relationships, classes, or a list, pivot to article keyword search first instead of treating discover as a relational query tool.

• "drug classes that interact with warfarin" -> use biomcp search article -k "drug classes that interact with warfarin" --type review --limit 5
• "genes regulated by MEF2 in the heart" -> use biomcp search article -k "genes regulated by MEF2 in the heart" --type review --limit 5, then biomcp get gene <symbol> once the literature or question gives you the concrete gene you actually need

Don't keyword-reformulate

Never do more than 3 article searches for one question. For iterative keyword searches, pass --json --session <token> so BioMCP can detect overlap across consecutive searches; the token is a local non-secret label, not a user ID. If two searches with different keywords return similar or empty results, follow the JSON _meta.suggestions[] ladder or change strategy entirely: inspect the previous result set with biomcp article batch <id1> <id2> ..., switch entity or source, narrow by year, or start with biomcp discover "<free text>".

Trial nicknames don't work in trial search

ClinicalTrials.gov usually does not index nicknames like CodeBreaK, COSMIC, BEACON, or KEYNOTE. Search by drug plus condition instead, or use biomcp search article -k "<trial nickname>" to recover the NCT ID first.

Don't use --type for niche topics

--type reduces recall to Europe PMC publication-type filtering today because PubTator3 and Semantic Scholar search results do not expose publication-type filtering. Use it for broad review questions with many results, not sparse or niche topics.

Use --drug on article search for drug-specific questions

When the question is about a specific drug's trial results, efficacy, or mechanism, add --drug <name> to search article. Without the drug filter, the key results paper often ranks too low to appear on the first page.

Batch syntax is entity-specific

biomcp article batch <pmid1> <pmid2> ... uses spaces between PMIDs. biomcp batch gene <gene1,gene2,...> and biomcp batch drug <drug1,drug2,...> use comma-separated IDs.

Output and evidence rules

• Quote multi-word IDs or names in commands.
• Do not invent sections, filters, or helper flags that biomcp list does not show.
• Treat empty structured regulatory drug results as signal for approved-drug questions, not as a CLI failure.
• Prefer review articles for synthesis questions and structured sections for direct facts.
• Use _meta.next_commands from JSON mode as the executable follow-up contract.
• For article search, _meta.suggestions[] may contain exact keyword entity matches with command, reason, and sections, or session loop-breaker suggestions with command and reason only. Multi-concept phrases and typed-filter searches should not produce direct entity suggestions.

Answer commitment

• Only add more commands if a needed claim is still unsupported. If one command already answers the question, stop searching and answer.
• If a structured section already contains the answer, use it. Anti-pattern: after biomcp get drug nivolumab regulatory shows Sponsor: BRISTOL MYERS SQUIBB, do not search articles just to confirm who developed nivolumab.
• If 1-2 papers you already fetched state the answer in the abstract or TLDR, answer from those papers instead of hunting for a third paper.
• If 3+ searches keep returning relevant papers, the answer is in what you already have or you need a different approach. If you keep reformulating the same search with different keywords, the answer is in what you already have or you need a different approach. Example: once repeated tau PET or European influenza vaccine searches keep surfacing relevant review papers, stop keyword-churning and extract the answer from those results.

Run biomcp skill list for worked examples.