Drug Pipeline

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

Pharmaceutical R&D Pipeline Intelligence for AI Agents — a lightweight MCP server that aggregates clinical trial data, FDA/EMA approvals, safety surveillance (FAERS), drug labels, patents, drug interactions, recalls, and publications through a unified API. Every output includes a verifiable source identifier (NCT ID, FDA Application Number, or PMID).

Not a replacement for IQVIA/EvaluatePharma. A real-time, publicly accessible intelligence layer that complements subscription databases.

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Quick Start

pip install git+https://github.com/DasClown/drug-pipeline-mcp.git

# Start MCP server (stdio)
drug-pipeline

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

Or deploy via Smithery — one click, no config.

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Tools (28)

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
get_trial_results	Trial outcomes — endpoints, adverse events, participant flow	ClinicalTrials.gov
get_trial_sites	Trial site locations — facilities, countries, geo distribution	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 Drugs@FDA
get_eu_approvals	EU/EMA authorization — 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
detect_safety_signals	Disproportionality screening (exploratory) — AE reporting ratios	openFDA FAERS
get_drug_label	FDA prescribing info — indications, boxed warnings, contraindications, dosing	openFDA Drug Labeling
get_dailymed_label	NIH drug label (OTC + Rx) — SPL set ID, version, DailyMed URL	DailyMed (NIH/NLM)
get_recalls	FDA drug recalls — Class I/II/III, reasons, dates, firms	openFDA Enforcement
get_patent_expiry	Patent & exclusivity — approval dates, market exclusivity estimates	openFDA
get_drug_interactions	Drug-drug interactions — FDA label + FAERS co-reported drugs	openFDA Labeling + FAERS
get_drug_pricing	US drug product ID — NDC codes, manufacturers, strength, form	openFDA NDC Directory
get_opentargets_drug	Drug-target MOA — mechanisms, targets, clinical stage, drug type	Open Targets (EMBL-EBI)
get_us_orphan_designations	US FDA Orphan Drug Designations — indication, status, exclusivity	MyChem.info
approved_for_condition	Find drugs by indication — which are EU-approved for a condition	EMA Daily XLSX
list_orphan_drugs	EU orphan drug designations — filter by therapeutic area	EMA Daily XLSX
list_biosimilars	EU biosimilars — filter by condition / therapeutic area	EMA Daily XLSX
list_loss_of_exclusivity	LOE timing — biosimilar competition by active substance	EMA + FDA
company_pipeline	Company R&D — trials grouped by phase + EU approval enrichment	ClinicalTrials.gov + EMA
search_publications	PubMed search for drug/trial publications	PubMed / NCBI
find_investigators	KOL / PI search — investigators by condition or drug	ClinicalTrials.gov + PubMed
detect_combination_therapies	Combination therapy detection — co-administered drugs in trials	ClinicalTrials.gov
compare_drugs	Head-to-head — FDA, EU, MOA, safety, patent across 2 drugs	Composite
drug_pipeline	Composite — drug info + FDA + EU + safety + label + signals + recalls + interactions + trials + pubs + patent	All sources
pipeline_landscape	Full pipeline for a condition — approved + Phase 3/2/1 + mechanisms + sponsors + pubs	Composite

⚠️ detect_safety_signals: Exploratory disproportionality screening — uses an approximate denominator, not a validated PRR. Not for regulatory or clinical use. See methodology note in code.

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Architecture

drug-pipeline-mcp/
├── drug_pipeline/
│   ├── __init__.py        # Version
│   ├── server.py          # MCP server (28 tools)
│   └── sources.py         # Data source fetchers (API aggregation layer)
├── drug_pipeline_cli.py   # CLI entry point
├── tests/                 # 61 unit tests (pytest)
├── pyproject.toml
└── README.md

Design philosophy: Lightweight API aggregation. No caching layer. No ML models. No predictions. Each tool makes real-time requests to a public API and returns structured data with source identifiers. The server is intentionally simple — it extracts, structures, and annotates, nothing more.

Limitations by design:

• Rate limits apply per source (openFDA: 10 req/sec, ClinicalTrials.gov: generous)
• EMA data sourced from a daily-updated XLSX register — format changes monitored manually
• FAERS data is spontaneous reporting, not incidence rates
• The server does not interpret, predict, or synthesize beyond what the sources provide

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Data Sources

Source	Data	Access
ClinicalTrials.gov	500K+ studies, phases, status, eligibility, results, site locations	✅ Always free
openFDA NDC Directory	Drug product ID, NDC codes, manufacturers	✅ Always free
openFDA FAERS	Adverse event reports, reactions, serious outcomes	✅ Always free
openFDA Drug Labeling	Prescribing info, interactions, contraindications	✅ Always free
openFDA Drugs@FDA	Approval history, submissions, orphan designations	✅ Always free
openFDA Enforcement	Recalls, market withdrawals, safety alerts	✅ Always free
RxNorm / RxNav	Drug identifiers, RxCUI, ATC classification	✅ Always free
PubMed / NCBI	Scientific publications, abstracts, PMIDs	✅ Always free
EMA Medicines Register	EU authorization status, ATC, orphan/biosimilar flags	✅ Always free
Open Targets (EMBL-EBI)	Drug-target mechanisms of action, clinical development stage	✅ Always free
DailyMed (NIH/NLM)	Drug labels (OTC + Rx), structured product labeling	✅ Always free
MyChem.info	US FDA Orphan Drug Designations	✅ Always free

All sources are publicly funded and freely accessible. No API keys, subscriptions, or licensing required.

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Verifiable Outputs

Every data point includes a direct link to its primary source:

Output Field	Example Source URL
NCT ID	https://clinicaltrials.gov/study/NCT03178617
FDA Application Number	https://www.accessdata.fda.gov/scripts/cder/daf/index.cfm?event=overview.process&ApplNo=NDA125456
PMID	https://pubmed.ncbi.nlm.nih.gov/37272535/
FDA Product NDC	https://www.accessdata.fda.gov/scripts/cder/ndc/
DailyMed SPL Set ID	https://dailymed.nlm.nih.gov/dailymed/drugInfo.cfm?setid=xxx

No calculated fields. No predictions. No estimates. The tool is an aggregator, not an oracle — it brings primary-source data into an AI agent's context so the LLM can apply reasoning, not so the server can produce answers.

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Testing & Quality

Check	Status
Unit tests	✅ 61 passing (pytest)
CI/CD	✅ Multi-Python matrix (3.10–3.13), Docker build, PyPI publish
Linting	✅ Ruff (zero warnings)
Formatting	✅ Black-compatible
Code coverage	Tracked in CI

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Regulatory Intelligence

Beyond drug-level approvals, this project provides multi-jurisdiction regulatory framework intelligence for pipeline analysis. See docs/local-regulation-2026.md for a comprehensive reference covering 7 jurisdictions:

• 🇺🇸 US IRA — Medicare Part D price negotiation (Sep 2026), Small Molecule Penalty (7 yr vs 13 yr)
• 🇩🇪 Germany AMNOG — Benefit assessment, 2026 reform with fixed effect-size thresholds
• 🇫🇷 France HAS/CEPS — SMR/ASMR ratings, 400–600 day access timelines
• 🇮🇹 Italy AIFA — 21 regional formularies, payback mechanisms
• 🇬🇧 UK MHRA/NICE — Post-Brexit ILAP pathway, £/QALY thresholds
• 🇯🇵 Japan PMDA/NHI — Sakigake designation, biennial price revision
• 🇨🇳 China NMPA/NRDL — Annual –61% price negotiation

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Example Agent Queries

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

"What are the safety signals for semaglutide?" → get_safety_data(drug_name="semaglutide") + detect_safety_signals(drug_name="semaglutide")

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

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

"What drugs are approved for non-small cell lung cancer in the EU?" → approved_for_condition(condition="non-small cell lung cancer")

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Client Integration

Claude Desktop

{
  "mcpServers": {
    "drug-pipeline": {
      "command": "python3",
      "args": ["-m", "drug_pipeline.server"]
    }
  }
}

Cursor / VS Code

{
  "mcpServers": {
    "drug-pipeline": {
      "command": "uvx",
      "args": ["drug-pipeline-mcp"]
    }
  }
}

HTTP / SSE (Remote)

pip install drug-pipeline-mcp[http]
drug-pipeline --http --port 8081

Connect at http://your-server:8081/sse.

Smithery

One-click deploy. No config needed.

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🤝 Getting Help & Contributing

Channel	Purpose
💬 GitHub Discussions	Questions before coding, feature ideas, community chat
🐛 GitHub Issues	Bug reports, confirmed feature requests
📖 CONTRIBUTING.md	Development setup, code style, testing

New contributors welcome. See CONTRIBUTING.md for setup instructions.

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License

MIT