MCP Tools for Healthcare

Model Context Protocol tools designed specifically for healthcare AI applications. Connect AI models to medical data sources, EHR systems, and clinical workflows seamlessly.

Built on the Model Context Protocol standard, our tools enable seamless integration between AI models and healthcare systems.

EHR Connector

Seamlessly integrate with FHIR/HL7 systems. Connect to Epic, Cerner, Allscripts, and other major EHR platforms.

Features:

  • FHIR R4 support
  • HL7 v2 integration
  • Real-time data sync
  • HIPAA compliant
Code Example
// Connect to EHR system
const ehr = await mcp.connect({
  provider: 'epic',
  endpoint: 'https://api.epic.com',
  credentials: {...}
});

// Fetch patient data
const patient = await ehr.getPatient(patientId);

Medical Imaging Analyzer

DICOM processing and analysis. X-ray, MRI, CT scan analysis with state-of-the-art AI models.

Features:

  • DICOM support
  • Multi-modal analysis
  • 99.9% accuracy
  • Real-time processing
Code Example
// Analyze medical image
const result = await mcp.analyzeImage({
  image: dicomFile,
  modality: 'xray',
  analysisType: 'fracture-detection'
});

Clinical Decision Engine

Evidence-based recommendations. Real-time clinical decision support powered by medical literature.

Features:

  • Evidence-based
  • Real-time recommendations
  • Literature integration
  • Risk assessment
Code Example
// Get clinical recommendations
const recommendations = await mcp.getRecommendations({
  patientData: {...},
  condition: 'diabetes',
  context: 'treatment-planning'
});

Patient Monitor

Real-time vital analysis. Continuous monitoring from wearables and medical devices.

Features:

  • Real-time monitoring
  • Wearable integration
  • Alert system
  • Trend analysis
Code Example
// Monitor patient vitals
const monitor = await mcp.startMonitoring({
  patientId: '123',
  devices: ['apple-watch', 'blood-pressure-monitor'],
  alertThresholds: {...}
});

Documentation Assistant

NLP for clinical notes. Automate documentation, extract insights, and structure unstructured data.

Features:

  • NLP processing
  • Auto-summarization
  • ICD-10 coding
  • Template generation
Code Example
// Process clinical notes
const structured = await mcp.processNotes({
  notes: rawText,
  outputFormat: 'structured',
  extractCodes: true
});

Drug Interaction Checker

Safety validation. Check drug interactions, allergies, and contraindications in real-time.

Features:

  • Drug interactions
  • Allergy checking
  • Contraindications
  • Dosage validation
Code Example
// Check drug interactions
const safety = await mcp.checkDrugSafety({
  medications: ['aspirin', 'warfarin'],
  patientAllergies: [...],
  conditions: [...]
});

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