An intelligent clinical decision support system that leverages the Model Context Protocol (MCP) to provide structured, auditable clinical recommendations.

Overview

An intelligent clinical decision support system that leverages the Model Context Protocol (MCP) to provide structured, auditable clinical recommendations. The system ingests unstructured clinical notes and generates evidence-based treatment plans with precise medication dosing calculations.

🎯 Core Features

• Clinical Note Parsing: Extracts structured patient data from unstructured text
• Condition Identification: Matches symptoms and assessments to medical conditions
• Medication Dosing: Calculates weight-based doses with safety constraints
• Treatment Planning: Generates comprehensive, evidence-based treatment plans
• Audit Trail: Provides transparent, reproducible clinical reasoning

🏥 Supported Conditions

• Pediatric Croup (Laryngotracheobronchitis)
• Adult Acute Asthma (Bronchospasm)
• COPD Exacerbation (Chronic Obstructive Pulmonary Disease)
• Community-Acquired Pneumonia (CAP)
• Paediatric Gastroenteritis (Dehydration management)

Why MCP over RAG?

• Deterministic Results: Medical decisions require reproducible, auditable outputs
• Structured Validation: Medical data needs strict input/output validation
• Performance: Direct tool calls are faster than semantic search Safety: Explicit logic is safer than AI interpretation for medical calculations
• Transparency: Clear reasoning chain for clinical decisions

Why JSON Files over Database?

• Simplicity: No database setup/configuration for MVP
• Version Control: Clinical data tracked in git with code
• Performance: Fast file reads from Lambda filesystem
• Cost: No database costs for MVP
• Development Speed: Instant data updates without deployment