BioMCP TS MCP Server
@yeyuan98
基本情報
BioMCP TS MCP Server について
A high-performance MCP server that gives LLMs access to 24 biomedical tools federated across 50+ upstream APIs — genes, variants, drugs, diseases, literature, and clinical trials in a single integration.
BioMCP TS MCP Server の設定
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"biomcp": {
"command": "npx",
"args": [
"biomcp"
]
}
}
}BioMCP TS MCP Server のツール
41Search for genes by symbol, name, or keyword
Get detailed gene information by symbol
Get diseases associated with a gene. Requires DISGENET_API_KEY environment variable for DisGeNET data; falls back to OpenTargets gene-disease associations when unavailable.
Find drugs targeting a gene
Find clinical trials for a gene
Find articles about a gene
Perform pathway enrichment analysis for a gene list
Search for variants. Use structured parameters for best results: - rsid: e.g. query="rs113488022" - HGVS: e.g. query="NM_004333.4:c.1799T>A" - Gene filter: e.g. gene="BRAF" with hgvsp="V600E" or consequence="missense" - ClinVar significance: e.g. significance="pathogenic" Do NOT use compound free-text like "BRAF V600E" — use separate gene and hgvsp parameters instead.
Get detailed variant information with optional sections. Core data (id, gene, rsid, significance) is always returned at the top level. Use sections to request additional data.
Get OncoKB annotations for a variant in a cancer gene. Requires ONCOKB_TOKEN environment variable.
Find clinical trials for a variant
Search for drugs by name, mechanism, or keyword
Get detailed drug information by name
Find clinical trials for a drug
Search for diseases by name, phenotype, or keyword
Get detailed disease information by ID
Get drugs for a disease via OpenTargets
Get clinical trials for a disease
Search literature across multiple backends with federated search and deduplication
Get article by PMID/PMCID/DOI. Citation: fast mode (~4s, 4 providers, auto-fallback to PubMed) or full mode (~15-30s, all 5 providers incl. PubMed). Forward citation lists come from Europe PMC, Semantic Scholar, and OpenCitations; Crossref provides counts and references only.
Search clinical trials by condition, intervention, or keyword
Get detailed trial information by NCT ID
Free-text concept resolution - find entities matching a free-text query
Get multiple entities in parallel
Access the Protein Data Bank (RCSB PDB) for macromolecular structure data. SEARCH: Provide "query" to find structures (e.g., "kinase inhibitor", "hemoglobin"). GET: Provide "pdb_id" to retrieve entry metadata with optional detail sections. DOWNLOAD: Provide "pdb_id" + download=true to save the structure file and get the file path.
Search patents worldwide (US, EP, WO, JP, and 100+ authorities). Quote exact multi-word concepts (e.g. "mRNA display") to avoid off-topic matches. Backend characters: ppubs = USPTO Public Search full-text conceptual search (US only, keyless, relevance-ranked; default US backend) | ops = EPO OPS worldwide bibliographic search over titles/abstracts (needs EPO_OPS_CONSUMER_KEY/EPO_OPS_CONSUMER_SECRET) | uspto_odp = US application metadata, bibliographic only but inventor/CPC/continuity-rich (needs USPTO_API_KEY) | google_patents = worldwide best-effort (often unavailable). Auto mode queries worldwide + ppubs concurrently; if ppubs fails hard it falls back to uspto_odp once (tagged with _note). Pass source to force a specific backend. Results are ranked by relevance by default (ppubs sort_by). Foundational prior art is auto-discovered via co-citation mining of the top results and returned in seminal_prior_art (surfaces seminal documents whose own vocabulary predates the query concept).
Get patent details by publication number (e.g. "US11027025B2", "EP3904939B1", "US20260240819A1"). Sections: abstract, claims (US fulltext via USPTO Public Search; EP/WO via EPO OPS), citations (backward + forward), family, classifications.
Search NCBI GEO (Gene Expression Omnibus) for functional genomics studies — expression microarrays, RNA-seq, and other high-throughput sequencing series. Queries accept plain terms ("breast cancer RNA-seq", "melanoma single cell") or NCBI field syntax ("GSE183947[Accession]"). Each result carries cross-links for chaining: sra_project → sra_get, bioproject, pubmed_ids → article_get, and accession → geo_get for full details.
Get the full SOFT record details for a GEO entry: series (GSE...), sample (GSM...), or platform (GPL...). A series detail includes summary, organisms, platform_ids, a sample preview, supplementary file URLs, and cross-references for chaining: sra → sra_get(SRP.../SRR...), pubmed_ids → article_get, samples → geo_get(GSM...), platform_ids → geo_get(GPL...). download=true additionally saves the first supplementary file (.gz/.csv/.txt, subject to max_bytes) to a local temp path and returns its path, size, and source URL.
Search NCBI's Sequence Read Archive (SRA) for sequencing experiments and runs. The query may be free text, an accession (SRP study, SRX experiment, SRR run, SRS sample), or NCBI field syntax ("RNA-SEQ AND Homo sapiens[Organism]"). Results list experiment/study/sample accessions, organism, library strategy, run count, and first_run_accession for chaining into sra_get.
Get full details for an NCBI SRA accession: SRR run (instrument, spots, bases, size), SRX experiment (library design), SRP study (experiment list), or SRS sample. Chain from geo_get (sra field) or sra_search (experiment_accession / first_run_accession). European (ERP/ERR) and DDBJ (DRP/DRR) accessions are NOT indexed in NCBI SRA — use ENA (https://www.ebi.ac.uk/ena) for those.
Search NCBI nucleotide records (GenBank/RefSeq/INSDC). Queries may be plain terms, an accession, or NCBI field syntax ("TP53[Gene Name] AND Homo sapiens[Organism]", "BRCA1[Gene Name]"). Results include accession.version, definition, length_bp, organism, and topology — chain accessions into genbank_get or genbank_genes.
Fetch a GenBank/RefSeq nucleotide record as text (GenBank flat file or FASTA). Whole-record fetches are capped at 2,000,000 bp — larger records require a seq_start/seq_stop region (1-based, inclusive, up to 10 Mb span; set strand=2 for a reverse-strand slice where seq_start > seq_stop — the region field echoes the request as given, while NCBI's text shows complement(min..max)). Output guard: sequence_text is truncated to its first 200,000 characters when oversized — request a narrower region for the full text.
Map a GenBank/RefSeq nucleotide accession to its NCBI Gene IDs (elink nuccore→gene). The returned gene_ids are entrezgene IDs usable directly with MyGene-backed gene tools (gene_get, gene_search). Useful bridge from a sequence record to gene-level annotation.
Get median gene expression across GTEx tissues (GTEx Analysis v10, 54 tissue sites, TPM, sorted highest first). Accepts an HGNC symbol (TP53) or Ensembl gene ID (ENSG00000141510, versioned or bare). Optionally filter to a single tissue via its tissueSiteDetailId (e.g. Brain_Cortex, Whole_Blood).
Get significant cis-eQTL associations for a gene in a specific GTEx tissue (GTEx Analysis v10): variant_id, p_value, and NES (effect direction/size), sorted by ascending p-value. tissue is a required GTEx tissueSiteDetailId (e.g. Whole_Blood, Brain_Cortex).
Resolve a gene in Ensembl terms for ANY Ensembl species (356 available): stable ID (ENSG…), symbol↔ID mapping, versioned identifier, canonical transcript, and coordinates on the current assembly (GRCh38 human, GRCm39 mouse, …). With expand=true, returns all transcripts with translation/protein IDs. Accepts an HGNC symbol (BRAF) or Ensembl gene ID (ENSG00000157764, versioned or bare — versions are resolved to the current record). Species accepts scientific names or aliases ('homo_sapiens'/'human', 'mus_musculus'/'mouse'). For rich human gene annotation (summary, pathways, drugs, diseases) use gene_get instead — this tool is the identifier/structure authority.
Find orthologues or paralogues of a gene across species (Ensembl Compara) — the cross-species gene mapping source in biomcp. Returns target stable IDs, species, taxonomy level, and percent identity, sorted by identity. Accepts an HGNC symbol or Ensembl gene ID; scope to one species with target_species ('mouse') or target_taxon (10090). Use it for conservation questions ('is this gene conserved?', 'what is the mouse orthologue of BRAF?').
Predict the functional consequence of a variant on demand via Ensembl VEP — works even for NOVEL variants absent from every database, and for non-human species. Input forms: HGVS c./p./g. notation ("NM_004333:c.1799T>A", "ENST00000288602:c.1799T>A") or a dbSNP rsID ("rs113488060"). Prefer HGVS over rsIDs when both are available — rsIDs are resolved through dbSNP's coordinate mapping, which can yield less specific consequences. Returns the most severe consequence plus per-transcript effects (impact, codon/amino-acid change, SIFT/PolyPhen where available) and co-located known variants (ClinVar/COSMIC IDs, gnomAD/1000G frequencies when present). For KNOWN human variants, variant_get additionally provides deep pre-computed scores (CADD, REVEL, AlphaMissense, ClinVar stars) — prefer it there.
Query what lives in a genomic interval on the current assembly (GRCh38 for human): genes/transcripts (stable IDs, symbols, biotypes) and known variants (rsIDs, alleles, consequence terms, clinical significance). Ideal for locus triage — "what genes and known variants sit in this GWAS hit interval?". Keep spans modest (<1 Mb recommended); output is capped at limit with a truncated marker. For sequence text use genbank_get; for entity-level annotation chain IDs into gene_get / variant_get.
Inspect and configure biomcp — unified observability and restricted controllability for every parameter. **What it covers:** three optional feature groups (database, analysis_r, analysis_biowasm) whose knobs live in the .biomcp.json project config file (written by this tool, loaded at server startup — a restart applies changes), plus every environment-only parameter (API keys, proxy, security boundaries), which is query-only. **Actions:** - status (default; call with {}): per-feature running state (with each feature's settable_keys), config file health, conflicts (e.g. an env var vetoing the file), pending-restart flags, dependency prerequisites, and parameter counts. The full parameter catalog is NOT inlined — use filter for detailed rows: 'file', 'env', a feature id ('analysis_r'), or a dotted-id prefix ('features.database'). - set: create/modify file parameters in one atomic batch. Enable/disable is just features.<group>.enabled. null removes a key (restores default). Sensitive keys (connection targets, mirrors) require confirm_sensitive=true. Nothing is written when any key is invalid (dry_run=true validates and diffs without writing). - reset: remove a feature section (target: feature id) or specific keys (target: [dotted ids]). **Hard rules:** environment parameters are never settable here (the response tells you how to set them in your client's env block); env var values are never displayed (masked: presence + fingerprint only); the file write is refused when the server's working directory is not a project root — the response then carries a paste-ready env block instead. **Examples:** {"action":"status"} · {"action":"status","filter":"features.analysis_r"} · {"action":"set","values":{"features.analysis_biowasm.enabled":true}} · {"action":"set","values":{"features.database.enabled":true,"features.database.type":"sqlite","features.database.sqlite_path":["data/geo.db"]}} · {"action":"set","values":{"features.analysis_r.mirror_url":null}} · {"action":"reset","target":"analysis_r"} Changes apply at server startup: finish dependency prerequisites first (see prerequisites in the response), then restart the client/session once, then re-call this tool with {} to verify running_now.
概要
Democratizing agentic access to bioinformatics and biopharmaceutical databases and analyses.
- Section-based federated access to 50+ bioinformatics, pharmaceutical, and patent databases
- Optional toolboxes for local database curation and dependency-free analysis with Bioconductor and SAM/BED/BCFtools — no R installation, C toolchain, or containers
- Concrete example vignettes, developed fully in the open
Install
npx -y biomcp doctor # diagnose a machine: Node gate, config health, feature gates, peer deps
npx biomcp # zero-config stdio MCP server (this is what MCP clients run); Node >= 22.13
「データと分析」の他のコンテンツ
App Store Tracker
Top In ItiOS App Store data for AI agents: chart rankings, app details, reviews, keywords, ads and revenue estimates for any app in any country.
AppGoat
App Store and Google Play data for agents: apps, reviews, keyword research, top charts, competitors and ASO audits.
LeadBoxer
Company and contact enrichment: identify the company behind an IP, get firmographics for a domain, and profile a work email.
Sugra API MCP
Sugra Systems, Inc.Official MCP server for the Sugra API, giving AI agents source-attributed access to 1,500+ endpoints across 36 data domains from 160+ primary sources. Covers markets, economics, company fundamentals, government, news, cl
AIsa
AIsaAIsa is one key for 950+ data APIs across SEO and AI visibility, finance, social, web search, sales and agent mail — the go-to-market data stack behind prospecting, competitor research and brand monitoring. Five tools ra
コメント