genomoncology

biomcp

Built by genomoncology 470 stars

What is biomcp?

BioMCP: Biomedical Model Context Protocol

How to use biomcp?

1. Install a compatible MCP client (like Claude Desktop). 2. Open your configuration settings. 3. Add biomcp using the following command: npx @modelcontextprotocol/biomcp 4. Restart the client and verify the new tools are active.
🛡️ Scoped (Restricted)
npx @modelcontextprotocol/biomcp --scope restricted
🔓 Unrestricted Access
npx @modelcontextprotocol/biomcp

Key Features

Native MCP Protocol Support
Real-time Tool Activation & Execution
Verified High-performance Implementation
Secure Resource & Context Handling

Optimized Use Cases

Extending AI models with custom local capabilities
Automating system workflows via natural language
Connecting external data sources to LLM context windows

biomcp FAQ

Q

Is biomcp safe?

Yes, biomcp follows the standardized Model Context Protocol security patterns and only executes tools with explicit user-granted permissions.

Q

Is biomcp up to date?

biomcp is currently active in the registry with 470 stars on GitHub, indicating its reliability and community support.

Q

Are there any limits for biomcp?

Usage limits depend on the specific implementation of the MCP server and your system resources. Refer to the official documentation below for technical details.

Official Documentation

View on GitHub

BioMCP

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

Description

BioMCP cuts through the usual biomedical data maze: one query reaches the sources that normally live behind different APIs, identifiers, and search habits. Researchers, clinicians, and agents use the same command grammar to search, focus, and pivot without rebuilding the workflow for each source. You get compact, evidence-oriented results across live public data plus local study analytics.

Features

  • Search the literature: search article fans out across PubTator3 and Europe PMC, deduplicates PMID/PMCID/DOI identifiers, and can add a Semantic Scholar leg when your filters support it.
  • Pivot without rework: move from a gene, variant, drug, disease, pathway, protein, or article straight into the next built-in view instead of rebuilding filters by hand.
  • Analyze studies locally: study commands cover local query, cohort, survival, compare, and co-occurrence workflows with native terminal, SVG, and PNG charts for downloaded cBioPortal-style datasets.
  • Follow the paper trail: article citations, article references, article recommendations, and article entities turn one known paper into a broader evidence map.
  • Enrich and batch: use biomcp enrich for top-level g:Profiler enrichment and biomcp batch for up to 10 focused get calls in one command.

Installation

PyPI tool install

uv tool install biomcp-cli
# or: pip install biomcp-cli

This installs the biomcp binary on your PATH.

Binary install

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

Claude Desktop extension (.mcpb)

Install BioMCP from the Anthropic Directory in Claude Desktop when that path is available for your environment. For local/manual setups, use the JSON MCP config below.

Install skills

Install guided investigation workflows into your agent directory:

biomcp skill install ~/.claude --force

MCP clients

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

Remote HTTP server

For shared or remote deployments:

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

Remote clients connect to http://127.0.0.1:8080/mcp. Probe routes are GET /health, GET /readyz, and GET /.

Runnable demo:

uv run --script examples/streamable-http/streamable_http_client.py

See Remote HTTP Server for the newcomer guide.

From source

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

Quick start

First useful query in under 30 seconds:

uv tool install biomcp-cli
biomcp health --apis-only
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

Entities and sources

EntityUpstream providers used by BioMCPExample
geneMyGene.info, UniProt, Reactome, QuickGO, STRING, GTEx, Human Protein Atlas, DGIdb, ClinGenbiomcp get gene BRAF pathways hpa
variantMyVariant.info, ClinVar, gnomAD fields via MyVariant, CIViC, Cancer Genome Interpreter, OncoKB, cBioPortal, GWAS Catalog, AlphaGenomebiomcp get variant "BRAF V600E" clinvar
articlePubMed, PubTator3, Europe PMC, PMC OA, NCBI ID Converter, Semantic Scholar (optional auth; S2_API_KEY recommended)biomcp search article -g BRAF --limit 5
trialClinicalTrials.gov API v2, NCI CTS APIbiomcp search trial -c melanoma -s recruiting
drugMyChem.info, EMA local batch, ChEMBL, OpenTargets, Drugs@FDA, OpenFDA, CIViCbiomcp get drug Keytruda regulatory --region eu
diseaseMyDisease.info, Monarch Initiative, MONDO, OpenTargets, Reactome, CIViCbiomcp get disease "Lynch syndrome" genes
pathwayReactome, KEGG, g:Profiler, Enrichr-backed enrichment sectionsbiomcp get pathway hsa05200 genes
proteinUniProt, InterPro, STRING, ComplexPortal, PDB, AlphaFoldbiomcp get protein P15056 complexes
adverse-eventOpenFDA FAERS, MAUDE, Recallsbiomcp search adverse-event --drug pembrolizumab
pgxCPIC, PharmGKBbiomcp get pgx CYP2D6 recommendations
gwasGWAS Catalogbiomcp search gwas --trait "type 2 diabetes"
phenotypeMonarch Initiative (HPO semantic similarity)biomcp search phenotype "HP:0001250"

Cross-entity helpers

Pivot between related entities without rebuilding filters.

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 views still reference Enrichr where that is the backing source.

Sections and progressive disclosure

Every get command supports selectable sections for focused output:

biomcp get gene BRAF                    # summary card
biomcp get gene BRAF pathways           # add pathway section
biomcp get gene BRAF hpa                # protein tissue expression + localization
biomcp get gene BRAF civic interactions # multiple sections
biomcp get gene BRAF all                # everything

biomcp get variant "BRAF V600E" clinvar population conservation
biomcp get article 22663011 tldr
biomcp get drug pembrolizumab label targets civic approvals
biomcp get drug Keytruda regulatory --region eu
biomcp get disease "Lynch syndrome" genes phenotypes variants
biomcp get trial NCT02576665 eligibility locations outcomes

In JSON mode, get responses expose _meta.next_commands for the next likely follow-ups and _meta.section_sources for section-level provenance. batch ... --json returns per-entity objects with the same metadata shape.

API keys

Most commands work without credentials. Optional keys improve rate limits or unlock optional enrichments:

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 ALPHAGENOME_API_KEY="..." # AlphaGenome variant effect prediction

search article, get article, article batch, get article ... tldr, and the explicit Semantic Scholar helpers all work without S2_API_KEY. With the key, BioMCP sends authenticated requests and uses a dedicated rate limit at 1 req/sec. Without it, BioMCP uses the shared unauthenticated pool at 1 req/2sec. --source still remains all|pubtator|europepmc in v1, so the S2 leg is automatic rather than directly selectable. References and recommendations can be empty for paywalled papers because of publisher elision in Semantic Scholar upstream coverage.

Configuration

Claude Desktop extension settings

The directory bundle exposes only the optional settings needed for the first reviewer-facing build:

Claude Desktop fieldRuntime env varPurpose
OncoKB TokenONCOKB_TOKENEnables biomcp variant oncokb "<gene> <variant>" therapy and level evidence
DisGeNET API KeyDISGENET_API_KEYEnables scored DisGeNET sections on gene and disease lookups
Semantic Scholar API KeyS2_API_KEYImproves reliability for article TLDR, citation, reference, and recommendation helpers

The first directory build exposes only those three optional settings. Advanced CLI-only env vars remain documented in API Keys for the general BioMCP CLI path.

Usage Examples

Public cross-entity overview

User prompt: Give me a low-noise overview of BRAF in melanoma.

Expected tool call: biomcp search all --gene BRAF --disease melanoma --counts-only

Expected behavior: Returns a cross-entity counts summary that orients the next command instead of dumping long detail tables.

Expected output: Counts-first summary with suggested next commands for the highest-yield entity follow-ups.

Public variant evidence

User prompt: Summarize ClinVar significance and population frequency for BRAF V600E.

Expected tool call: biomcp get variant "BRAF V600E" clinvar population

Expected behavior: Retrieves the focused variant card, ClinVar section, and population-frequency data in one read-only call.

Expected output: Variant summary, ClinVar significance details, and gnomAD population frequencies.

Credentialed OncoKB example

User prompt: Show OncoKB therapy evidence for BRAF V600E.

Expected tool call: biomcp variant oncokb "BRAF V600E"

Expected behavior: Uses ONCOKB_TOKEN when configured and otherwise returns helpful guidance about the missing credential.

Expected output: Therapy and level evidence when ONCOKB_TOKEN is set, or a clear setup hint when it is not.

Credentialed DisGeNET example

User prompt: Show scored DisGeNET associations for TP53.

Expected tool call: biomcp get gene TP53 disgenet

Expected behavior: Uses DISGENET_API_KEY to retrieve the scored gene-disease association section.

Expected output: Ranked disease-association table with evidence counts and scores when DISGENET_API_KEY is configured.

Privacy Policy

BioMCP does not add telemetry, analytics, or remote log upload. Review the full privacy statement at https://biomcp.org/policies/.

Multi-worker deployment

BioMCP rate limiting is process-local. For many concurrent workers, run one shared Streamable HTTP biomcp serve-http endpoint so all workers share a single limiter budget:

biomcp serve-http --host 0.0.0.0 --port 8080

Remote clients should connect to http://<host>:8080/mcp. Lightweight process probes are available at GET /health, GET /readyz, and GET /.

Skills

BioMCP ships an embedded agent guide instead of a browsable in-binary catalog. Use biomcp skill to read the embedded BioMCP guide, then install it into your agent directory when you want local copies of the workflow references:

biomcp skill
biomcp skill install ~/.claude --force

See Skills for supported install targets, installed files, and legacy compatibility notes.

Local study analytics

study is BioMCP's local analysis family for downloaded cBioPortal-style datasets. The 12 remote entity commands query upstream APIs for discovery and detail; study commands work on local datasets when you need per-study query, cohort, survival, comparison, or co-occurrence workflows.

Use study download to fetch a dataset into your local study root. Set BIOMCP_STUDY_DIR when you want an explicit dataset location for reproducible scripts and demos; if it is unset, BioMCP falls back to its default study root.

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

See the CLI reference for the full study command family and dataset prerequisites.

Ops

biomcp version          # show version and build info
biomcp health           # inspect API connectivity plus local EMA/cache readiness
biomcp update           # self-update to latest release
biomcp update --check   # check for updates without installing
biomcp uninstall        # remove biomcp from ~/.local/bin

Support

Documentation

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.

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.

License

MIT

Global Ranking

-
Trust ScoreMCPHub Index

Based on codebase health & activity.

Manual Config

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