metadata

title: Pharmacist MCP
emoji: 💊
colorFrom: blue
colorTo: green
sdk: gradio
app_file: app.py
pinned: false
license: apache-2.0
tags:
  - pharmacology
  - clinical-pharmacy
  - healthcare
  - drug-information
  - calculator
  - gradio
  - mcp-server-track
sdk_version: 5.33.1

Pharmacist MCP Server

A comprehensive Model Context Protocol (MCP) server providing pharmaceutical and clinical decision support tools for healthcare applications. Two excample videos demonstrating usage can be found here and here.

🚀 Features

Drug Information & Safety

Adverse Event Search: Query FAERS database for drug safety reports
Drug Label Warnings: FDA boxed warnings, contraindications, and interactions
Drug Recalls: Recent FDA recall information
Pregnancy & Lactation: Comprehensive safety information with fallback data
Dose Adjustments: Renal and hepatic dosing guidance
LiverTox Integration: Hepatotoxicity information from NIH database

Advanced ADR Analysis (NEW!)

Enhanced FAERS Search: Advanced filtering by demographics, seriousness, and outcomes
Naranjo Probability Scale: Automated causality assessment for adverse drug reactions
Disproportionality Analysis: Signal detection using PRR, ROR, and IC methods
Case Similarity Analysis: Find similar adverse event cases
Temporal Analysis: Time-to-onset patterns and reporting trends

Clinical Calculators

Creatinine Clearance: Cockcroft-Gault equation
eGFR: CKD-EPI equation with CKD staging
Child-Pugh Score: Liver function assessment
BMI Calculator: Body mass index and weight categories
Ideal Body Weight: Devine formula
Dosing Weight: Recommendations for medication dosing
Drug Burden Index (DBI): Anticholinergic and sedative burden assessment

Utility Functions

Brand to Generic Lookup: International drug name conversion
Unit Conversions: Creatinine units (mg/dL ↔ μmol/L)
Cache Management: Performance optimization with TTL caching
Health Monitoring: Server status and performance metrics

🧬 ADR Analysis Capabilities

Pharmacovigilance Tools

The server now includes comprehensive adverse drug reaction (ADR) analysis tools suitable for clinical decision support and pharmacovigilance:

1. Enhanced FAERS Search

# Search with demographic filters
enhanced_faers_search(
    drug_name="warfarin",
    adverse_event="bleeding", 
    age_range=">65",
    gender="2",  # female
    serious_only=True
)

2. Naranjo Causality Assessment

# Automated causality scoring
calculate_naranjo_score(
    adverse_reaction_after_drug="yes",
    reaction_improved_after_stopping="yes",
    # ... 10 standardized questions
)
# Returns: Score, probability (Definite/Probable/Possible/Doubtful)

3. Signal Detection

# Disproportionality analysis for signal detection
disproportionality_analysis(
    drug_name="aspirin",
    adverse_event="gastrointestinal bleeding"
)
# Returns: PRR, ROR, IC with confidence intervals

📊 Performance Improvements

Reduced API timeouts: 3-5s instead of 10s for better responsiveness
Enhanced error handling: Graceful degradation with meaningful error messages
Improved caching: Smart cache management with statistics
Input validation: Comprehensive bounds checking and data validation

🔧 Installation

# Clone the repository
git clone <repository-url>
cd pharmacist_mcp

# Install dependencies
pip install -r requirements.txt

# Run the server
python app.py

📋 Requirements

Python 3.8+
Internet connection for API access
Dependencies listed in requirements.txt

🧪 Testing

Run the comprehensive test suite:

# Test core ADR analysis algorithms
python test_disproportionality.py

# Test individual components
python -c "from adr_analysis import calculate_naranjo_score; print(calculate_naranjo_score(...))"

🔗 API Endpoints

MCP Functions Available:

Drug Safety & Information

search_adverse_events_mcp(drug_name, limit)
fetch_event_details_mcp(event_id)
drug_label_warnings_mcp(drug_name)
drug_recalls_mcp(drug_name, limit)
drug_pregnancy_lactation_mcp(drug_name)
drug_dose_adjustments_mcp(drug_name)
drug_livertox_summary_mcp(drug_name)

ADR Analysis (NEW!)

enhanced_faers_search_mcp(drug_name, adverse_event, age_range, gender, serious_only, limit)
calculate_naranjo_score_mcp(...10 parameters...)
disproportionality_analysis_mcp(drug_name, adverse_event, background_limit)
find_similar_cases_mcp(reference_case_id, similarity_threshold, limit)
temporal_analysis_mcp(drug_name, adverse_event, limit)

Clinical Calculators

calculate_creatinine_clearance_mcp(age, weight_kg, serum_creatinine, is_female)
calculate_egfr_mcp(age, serum_creatinine, is_female, is_black)
calculate_child_pugh_score_mcp(bilirubin, albumin, inr, ascites, encephalopathy)
calculate_bmi_mcp(weight_kg, height_cm)
calculate_ideal_body_weight_mcp(height_cm, is_male)
recommend_dosing_weight_mcp(actual_weight, height_cm, is_male)
calculate_drug_burden_index_mcp(drug_list, route)

Utilities

brand_to_generic_lookup_mcp(brand_name, prefer_countries)
convert_creatinine_units_mcp(value, from_unit, to_unit)
get_cache_stats_mcp()
health_check_mcp()

📚 Data Sources

FAERS: FDA Adverse Event Reporting System
FDA Drug Labels: Official prescribing information
LiverTox: NIH hepatotoxicity database
Drug Brand Database: International brand name mappings

⚠️ Important Notes

This tool is for informational purposes only
Always consult official prescribing information
Results should be interpreted by qualified healthcare professionals
FAERS data has inherent limitations and reporting biases
Pharmacovigilance analysis requires clinical expertise