BioMCP: Turn Your AI Into a Biomedical Research Powerhouse

Stop wrestling with PubMed's arcane query syntax or hunting through ClinicalTrials.gov's labyrinthine interface. BioMCP gives your AI direct access to the biomedical databases you actually need – with natural language queries that just work.

Skip the Database Juggling Act

You know the drill: one syntax for PubMed, another for ClinicalTrials.gov, yet another for genomic databases. Each with its own authentication, rate limits, and quirks. BioMCP unifies them all behind a single MCP interface that speaks your language.

# Instead of this mess across multiple APIs...
pubmed_query = '("BRAF"[Gene] AND "melanoma"[MeSH]) AND "2023"[PDAT]'
trials_query = 'condition="Melanoma" AND intervention="BRAF inhibitor"'
variant_query = 'q=BRAF&assembly=GRCh38&significance=pathogenic'

# Do this:
search(query="gene:BRAF AND trials.condition:melanoma AND articles.date:>2023")

What You Get Access To

Literature Sources:

• PubMed/PubTator3 with entity annotations
• bioRxiv/medRxiv preprints
• Europe PMC full-text articles

Clinical & Genomic Data:

• ClinicalTrials.gov with real-time matching
• MyVariant.info consolidated annotations
• TCGA/GDC cancer genomics
• 1000 Genomes population data

All queryable through one consistent interface.

Real-World Time Savers

Before BioMCP: Your AI says "I'd need to search multiple databases to find BRAF mutation studies in melanoma patients from recent clinical trials..."

With BioMCP: Your AI directly queries and returns structured results from PubMed, ClinicalTrials.gov, and genomic databases in seconds.

Systematic Research Planning:

# AI can now think through complex biomedical queries systematically
search(
    domain="thinking",
    thought="Need to analyze BRAF mutations in melanoma across literature, trials, and genomic data",
    nextThoughtNeeded=True
)

Cross-Database Queries:

# Find pathogenic BRAF variants with associated clinical trials
search(query="gene:BRAF AND variants.significance:pathogenic AND trials.status:recruiting")

# Recent publications on specific interventions
search(query="trials.intervention:pembrolizumab AND articles.date:>2023 AND articles.journal:oncology")

Setup That Actually Works

For Claude Desktop users:

{
  "mcpServers": {
    "biomcp": {
      "command": "uv",
      "args": ["run", "--with", "biomcp-python", "biomcp", "run"]
    }
  }
}

Restart Claude Desktop. Start asking biomedical questions. That's it.

For Python developers:

pip install biomcp-python
biomcp run  # MCP server ready

CLI for direct database access:

# Skip the GUI entirely
biomcp trial search --condition "lung cancer" --phase PHASE3
biomcp variant search --gene TP53 --significance pathogenic
biomcp article search --gene BRAF --disease melanoma --no-preprints

Why This Beats Building Your Own

You could spend months figuring out each database's API, handling authentication, managing rate limits, and parsing their different response formats. Or you could install BioMCP and have structured access to all of them in minutes.

The unified query language alone saves hours of documentation diving. Need to search across trials and literature simultaneously? That's one query instead of coordinating multiple API calls.

Production-Ready Features

• MCP Review Certified - follows best practices, thoroughly tested
• Enterprise version available (OncoMCP) with HIPAA compliance
• Multiple installation methods - pip, uv, Docker, direct from source
• Comprehensive CLI for automation and scripting
• Structured responses your code can actually parse

Perfect for biotech startups, research institutions, or any developer building AI applications that need authoritative biomedical data. Your AI gets the specialized knowledge it needs, and you get back to building instead of integrating APIs.

Ready to give your AI a biomedical brain upgrade? The setup takes 2 minutes, and the first query will convince you this belongs in your toolkit.