Biomcp

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.

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.

Source: genomoncology/biomcp — distributed by TomeVault.