anandkiran2007/ahl-mcp-server
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This project is an open-source Model Context Protocol (MCP) server that connects to mocked AWS HealthLake data sources and provides structured, standardized context bundles for clinical models.
🏥 MCP Server for AWS HealthLake (Mocked)
This project is an open-source Model Context Protocol (MCP) server that connects to (mocked) AWS HealthLake data sources and provides structured, standardized context bundles for clinical models.
✅ Features
- Mocked AWS HealthLake APIs (FHIR-based)
- Context bundling per MCP spec (FHIR + NLP)
- Model registration and tailored context delivery
- Mocked model invocation endpoint
- Audit logging
- Optional
USE_AWSflag for future AWS integration
🚀 Quick Start
1. Clone or Download
unzip mcp-server.zip
cd ahl-mcp-server
2. Install Python Dependencies
python3 -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
pip install -r requirements.txt
3. Run Locally (Mock Mode)
uvicorn app.main:app --reload
Visit: http://localhost:8000/docs
🔁 Endpoints
📦 MCP Endpoints
| Endpoint | Method | Description |
|---|---|---|
/context/{patient_id} | GET | Get context bundle |
/models/register | POST | Register model info |
/models/{model_id}/context/{patient_id} | GET | Tailored context |
/model/invoke/{model_id}?patient_id=... | POST | Mock model prediction |
🧪 Mock HealthLake Endpoints
| Endpoint | Method | Description |
|---|---|---|
/ahl/Patient | POST | Create patient |
/ahl/Patient/{id} | GET | Get patient |
/ahl/Condition?patient=... | GET | Get conditions |
/ahl/MedicationRequest?patient=... | GET | Get meds |
/ahl/Observation?patient=... | GET | Get labs |
/ahl/mock/add_* | POST | Add mock data (condition/med/obs) |
⚙️ Switching Between Mock and AWS Mode
By default, the app runs in mock mode.
To prepare for future AWS integration:
export USE_AWS=true
Note: AWS mode is not implemented yet but ready for integration.
🧪 Run Tests
pytest tests/
📂 Folder Structure
app/
├── api/ # API endpoints
├── core/ # Config and logging
├── fhir/ # Placeholder for FHIR connector
├── models/ # Pydantic models
├── nlp/ # NLP mock enhancer
├── services/ # Context resolver, policy logic
├── main.py # FastAPI entry
infra/
tests/ # Test cases
schemas/ # MCP JSON schema
.env
requirements.txt
📜 License
MIT License
🧠 Coming Soon
- AWS HealthLake integration (
boto3) - Amazon Comprehend Medical / Bedrock models
- Dockerfile + ECS deployment
- Real-time cohort search
- SMART-on-FHIR authentication