💊 drug-pipeline-mcp

Pharmaceutical R&D Pipeline Intelligence for AI Agents — Clinical trials, FDA approvals, drug information & publications in one MCP server.

No hallucination. Every output traces to a source NCT ID, FDA application number, or PMID.

Quick Start

pip install git+https://github.com/DasClown/drug-pipeline-mcp.git
# or try it on Smithery: https://smithery.ai/servers/crop-mcp/drug-pipeline

# Start MCP server (stdio)
drug-pipeline

# Or HTTP mode for remote access
pip install drug-pipeline-mcp[http]
drug-pipeline --http --port 8081

Tools (16)

Tool	What it does	Data Source
`search_trials`	Search clinical trials by condition, phase, status, sponsor	ClinicalTrials.gov
`get_trial_detail`	Full protocol for a specific NCT (eligibility, outcomes, locations)	ClinicalTrials.gov
`lookup_drug`	Drug info: active ingredients, strength, ATC classification, NDC	openFDA + RxNorm
`get_approvals`	FDA approval history with submission dates and status	openFDA
`get_eu_approvals`	EU/EMA authorization status — brand names, ATC, status, orphan/biosimilar flags	EMA Daily XLSX
`get_safety_data`	FAERS adverse event reports — top reactions, serious outcomes, total count	openFDA FAERS
`approved_for_condition`	Find drugs by indication — which drugs are EU-approved for a condition	EMA Daily XLSX
`get_trial_results`	Trial results — outcome measures, adverse events, baseline, participant flow	ClinicalTrials.gov
`list_orphan_drugs`	EU orphan drug designations — filter by therapeutic area	EMA Daily XLSX
`company_pipeline`	Company R&D pipeline — all trials grouped by phase + EU approval status	ClinicalTrials.gov + EMA
`search_publications`	PubMed search for drug/trial publications	PubMed / NCBI
`get_drug_label`	FDA drug label — indications, boxed warnings, contraindications, dosing	openFDA Drug Labeling
`get_recalls`	FDA drug recalls — Class I/II/III, reasons, dates, recalling firms	openFDA Enforcement
`detect_safety_signals`	PRR safety signal detection — disproportionate adverse event analysis	openFDA FAERS
`get_patent_expiry`	Patent & exclusivity info — approval dates, market exclusivity estimates	openFDA
`drug_pipeline`	Composite — drug info + FDA + EU + safety + label + signals + recalls + trials + pubs + patent	All sources

Example Agent Queries

"What's in the pipeline for GLP-1 agonists?" → drug_pipeline(drug_name="semaglutide") → ATC class, FDA status, 10+ trials, publications

"Which companies have Phase 3 trials for non-small cell lung cancer?" → search_trials(condition="non-small cell lung cancer", phase="PHASE3", status="RECRUITING")

"Is pembrolizumab approved in the EU vs US?" → get_approvals(drug_name="Keytruda") → FDA submission history with dates → get_eu_approvals(drug_name="Keytruda") → EU authorization status

"What are the safety signals for semaglutide?" → get_safety_data(drug_name="semaglutide") → 6,027 FAERS reports, top reactions: Nausea (862), Vomiting (750) → detect_safety_signals(drug_name="semaglutide") → PRR analysis, disproportionate signals

"What does the label say for Keytruda?" → get_drug_label(drug_name="Keytruda") → indications, boxed warnings, contraindications, dosing

"Are there recalls for Tylenol?" → get_recalls(drug_name="Tylenol") → recall dates, reasons, classification, firms

"When does the patent for Keytruda expire?" → get_patent_expiry(drug_name="Keytruda") → approval dates, exclusivity information

"What drugs are approved for non-small cell lung cancer?" → approved_for_condition(condition="non-small cell lung cancer") → 82 drugs (Keytruda, Tagrisso, Opdivo, Tecentriq, ...)

"What are the eligibility criteria for NCT03178617?" → get_trial_detail(nct_id="NCT03178617")

Example Output (drug_pipeline)

{
  "status": "ok",
  "query": {"drug_name": "semaglutide"},
  "drug_info": {
    "atc_classification": {"code": "A10BJ", "name": "GLP-1 analogues"},
    "rxcui": "1991302",
    "products": [{"brand_name": "Ozempic", "generic_name": "semaglutide", "labeler": "Novo Nordisk"}]
  },
  "clinical_trials": { "results": [ ... ] },
  "publications": { "total_count": 846, "returned_count": 5 },
  "data_sources": ["openFDA", "RxNorm", "PubMed", "clinicaltrials.gov"]
}

Architecture

drug-pipeline-mcp/
├── drug_pipeline/
│   ├── __init__.py        # Version
│   ├── server.py          # MCP server (16 tools)
│   └── sources.py         # Data source fetchers
├── drug_pipeline_cli.py   # CLI entry point
├── pyproject.toml
└── README.md

No machine learning. No predictions. Only structured synthesis of verified primary sources.

Data Sources

Source	Data	Free
ClinicalTrials.gov	500K+ studies, phases, status, eligibility, results	✅ Always free
openFDA Drug Approvals	FDA approvals, NDC directory, submissions	✅ Always free
openFDA FAERS	Adverse event reports, reactions, outcomes	✅ Always free
RxNorm / RxNav	Drug identifiers, ATC classification	✅ Always free
PubMed / NCBI	Scientific publications	✅ Always free
EMA Medicines Register	EU authorization status, ATC, orphan/biosimilar flags, therapeutic areas	✅ Always free

Anti-Hallucination

Every result includes:

NCT ID → https://clinicaltrials.gov/study/NCT...
FDA Application Number → https://www.accessdata.fda.gov/...
PMID → https://pubmed.ncbi.nlm.nih.gov/PMID...

No calculated fields, no predictions, no "ungefähre" estimates.

Language

All output is in English (JSON field names, descriptions, results). The server can be configured via the language parameter on Smithery for future localization support.

License

MIT

drug-pipeline-mcp