Drug Pipeline

CI Docker Smithery Python 3.10+ License: MIT PyPI GitHub stars

Pharmaceutical R&D Pipeline Intelligence for AI Agents — Clinical trials, FDA/EMA approvals, safety data, drug interactions, drug labels, recalls, patents & 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 (17)

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
get_drug_interactions	Drug-drug interactions — FDA label interactions + FAERS co-reported drugs	openFDA Labeling + FAERS
drug_pipeline	Composite — drug info + FDA + EU + safety + label + signals + recalls + interactions + 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