BioMCP

One binary. One grammar. Evidence from the biomedical sources you already trust.

BioMCP replaces the usual routine of jumping between database sites, auth schemes, and API docs with one command surface for researchers, clinicians, and agents. Search, drill into detail, pivot to the next entity, and keep the output compact enough to stay useful. When public APIs are not enough, the same binary also runs local study analytics on downloaded cBioPortal datasets.

Install

PyPI tool install

uv tool install biomcp-cli
# or, inside an active Python environment:
# pip install biomcp-cli

Install the biomcp-cli package, then use biomcp for the commands shown throughout the docs.

Binary install

curl -fsSL https://biomcp.org/install.sh | bash

Install skills

Install guided investigation workflows into your agent directory:

biomcp skill install ~/.claude --force

For Claude Desktop / Cursor / MCP clients

{
  "mcpServers": {
    "biomcp": {
      "command": "biomcp",
      "args": ["serve"]
    }
  }
}

Remote HTTP server

For shared or remote deployments, start BioMCP over Streamable HTTP instead of stdio:

biomcp serve-http --host 127.0.0.1 --port 8080

Remote clients connect to http://127.0.0.1:8080/mcp. Probe routes are /health, /readyz, and /. See Remote HTTP Server for setup details, getting-started/remote-http.md in the docs tree, and demo/streamable_http_client.py for a runnable client example.

From source

make install
"$HOME/.local/bin/biomcp" --version

Quick start

Install to first result in under 30 seconds:

uv tool install biomcp-cli
biomcp health --apis-only
biomcp discover "chest pain"
biomcp list gene
biomcp search all --gene BRAF --disease melanoma  # unified cross-entity discovery
biomcp get gene BRAF pathways hpa

Command grammar

search <entity> [filters]    → discovery
discover <query>            → concept resolution before entity selection
get <entity> <id> [sections] → focused detail
<entity> <helper> <id>       → cross-entity pivots
enrich <GENE1,GENE2,...>     → gene-set enrichment
batch <entity> <id1,id2,...> → parallel gets
search all [slot filters]    → counts-first cross-entity orientation

Feature highlights

• Search the literature: search article fans out across PubTator3 and Europe PMC, deduplicates identifiers, and can add a Semantic Scholar leg when your filters support it.
• Resolve messy queries: biomcp discover turns aliases, brands, symptoms, and pathway names into the right entity before you commit to a typed command.
• Pivot across entities: move from a known gene, variant, drug, disease, pathway, protein, or article into trials, articles, drugs, pathways, structures, or article graph helpers without rebuilding context.
• Analyze studies locally: study commands cover cohort analytics and native terminal, SVG, and PNG charts for downloaded cBioPortal-style datasets.
• Follow the paper trail: article citations, article references, article recommendations, and article entities expand one paper into its surrounding evidence with optional Semantic Scholar auth.
• Enrich and batch: biomcp enrich uses g:Profiler, and biomcp batch runs up to 10 focused get calls with shared JSON metadata.

Entities and sources

Entity	Upstream providers used by BioMCP	Example
gene	MyGene.info, UniProt, Reactome, QuickGO, STRING, GTEx, Human Protein Atlas, DGIdb, ClinGen	biomcp get gene BRAF pathways hpa
variant	MyVariant.info, ClinVar, gnomAD fields via MyVariant, CIViC, Cancer Genome Interpreter, OncoKB, cBioPortal, GWAS Catalog, AlphaGenome	biomcp get variant "BRAF V600E" clinvar
article	PubMed, PubTator3, Europe PMC, PMC OA, NCBI ID Converter, Semantic Scholar (optional auth; S2_API_KEY recommended)	biomcp search article -g BRAF --limit 5
trial	ClinicalTrials.gov API v2, NCI CTS API	biomcp search trial -c melanoma -s recruiting
drug	MyChem.info, EMA local batch, ChEMBL, OpenTargets, Drugs@FDA, OpenFDA, CIViC	biomcp get drug Keytruda regulatory --region eu
disease	MyDisease.info, Monarch Initiative, MONDO, OpenTargets, Reactome, CIViC	biomcp get disease "Lynch syndrome" genes
pathway	Reactome, KEGG, g:Profiler, Enrichr-backed enrichment sections	biomcp get pathway hsa05200 genes
protein	UniProt, InterPro, STRING, ComplexPortal, PDB, AlphaFold	biomcp get protein P15056 complexes
adverse-event	OpenFDA FAERS, MAUDE, Recalls	biomcp search adverse-event --drug pembrolizumab
pgx	CPIC, PharmGKB	biomcp get pgx CYP2D6 recommendations
gwas	GWAS Catalog	biomcp search gwas --trait "type 2 diabetes"
phenotype	Monarch Initiative (HPO semantic similarity)	biomcp search phenotype "HP:0001250"

Cross-entity helpers

See the cross-entity pivot guide for when to use a helper versus a fresh search.

biomcp variant trials "BRAF V600E" --limit 5
biomcp variant articles "BRAF V600E"
biomcp drug adverse-events pembrolizumab
biomcp drug trials pembrolizumab
biomcp disease trials melanoma
biomcp disease drugs melanoma
biomcp disease articles "Lynch syndrome"
biomcp gene trials BRAF
biomcp gene drugs BRAF
biomcp gene articles BRCA1
biomcp gene pathways BRAF
biomcp pathway drugs R-HSA-5673001
biomcp pathway drugs hsa05200
biomcp pathway articles R-HSA-5673001
biomcp pathway trials R-HSA-5673001
biomcp protein structures P15056
biomcp article entities 22663011
biomcp article citations 22663011 --limit 3
biomcp article references 22663011 --limit 3
biomcp article recommendations 22663011 --limit 3

Gene-set enrichment

biomcp enrich BRAF,KRAS,NRAS --limit 10

Top-level biomcp enrich uses g:Profiler. Gene enrichment sections inside other entity pages still describe Enrichr where that is the source.

API keys

Most commands work without credentials. Optional keys improve rate limits:

export NCBI_API_KEY="..."        # PubTator, PMC OA, NCBI ID converter
export S2_API_KEY="..."          # Optional Semantic Scholar auth; dedicated quota at 1 req/sec
export OPENFDA_API_KEY="..."     # OpenFDA rate limits
export NCI_API_KEY="..."         # NCI CTS trial search (--source nci)
export ONCOKB_TOKEN="..."        # OncoKB variant helper
export UMLS_API_KEY="..."        # discover crosswalk enrichment
export ALPHAGENOME_API_KEY="..." # AlphaGenome variant effect prediction

Data Sources and Licensing

BioMCP is MIT-licensed. It performs on-demand queries against upstream providers instead of vendoring or mirroring their datasets, but upstream terms govern reuse of retrieved results.

Some providers are fully open, some BioMCP features require registration or API keys, and some queryable sources still impose notable reuse limits. The two biggest cautions are KEGG, which distinguishes academic and non-academic use, and COSMIC, which BioMCP keeps indirect-only because its licensing model is incompatible with a direct open integration.

Use Source Licensing and Terms for the per-source breakdown and API Keys for setup steps and registration links.

Skills

BioMCP ships an embedded guide for agent workflows rather than a built-in catalog. Read it with biomcp skill, install it with biomcp skill install ~/.claude --force, and see Skills for the current workflow and legacy notes.

Local study analytics

study is BioMCP's local analysis family for downloaded cBioPortal-style datasets. The 12 remote entity commands handle live API-backed discovery and detail; study commands cover local query, cohort, survival, compare, and co-occurrence workflows.

export BIOMCP_STUDY_DIR="$HOME/.local/share/biomcp/studies"
biomcp study download msk_impact_2017
biomcp study query --study msk_impact_2017 --gene TP53 --type mutations --chart bar --theme dark --palette wong -o docs/blog/images/tp53-mutation-bar.svg

Documentation

• Installation
• First Query
• Search All Workflow
• BioASQ Benchmark
• Discover
• Source Licensing and Terms
• Data Sources
• Quick Reference
• Troubleshooting

Citation

If you use BioMCP in research, cite it via CITATION.cff. GitHub also exposes Cite this repository in the repository sidebar when that file is present.

License

MIT