MediLinkAI
Clinical decision-support MCP server that lets AI agents reason over live FHIR patient data for medication review, appointment scheduling, and care gap identification.
README
Healthcare AI Superpower — MCP Server
Prompt Opinion · Agents Assemble Hackathon Clinical decision-support tools for any AI agent, powered by FHIR R4 and the Model Context Protocol.
What This Does
AI agents on the Prompt Opinion platform can call this MCP server to reason over live FHIR patient data without ever handling EHR credentials directly. The platform bridges the SMART on FHIR session into the server via the ai.promptopinion/fhir-context extension — the agent just asks a question, and this server handles the rest.
Five clinical tools, one endpoint:
| Tool | Clinical Use Case |
|---|---|
fhir_query |
Raw FHIR R4 resource retrieval (any resource type) |
medication_review |
Drug interactions · Beers Criteria · duplicate therapy · missing safety labs |
summarize_clinical_notes |
Structured extraction from FHIR DocumentReference notes |
schedule_appointment |
List, create, or cancel FHIR Appointment resources |
identify_care_gaps |
HEDIS · CMS · USPSTF quality gap identification |
Live Endpoints
| URL | |
|---|---|
| MCP Server | https://3a36e605-0c25-4400-ba89-a8f448f14c7b-00-3wj4nqft3ggq.sisko.replit.dev/api/mcp |
| Tools Listing | https://3a36e605-0c25-4400-ba89-a8f448f14c7b-00-3wj4nqft3ggq.sisko.replit.dev/api/mcp/tools |
| Health Check | https://3a36e605-0c25-4400-ba89-a8f448f14c7b-00-3wj4nqft3ggq.sisko.replit.dev/api/healthz |
| Demo Dashboard | https://3a36e605-0c25-4400-ba89-a8f448f14c7b-00-3wj4nqft3ggq.sisko.replit.dev/ |
Architecture
Prompt Opinion Platform
│
│ initialize → detects ai.promptopinion/fhir-context extension
│ tool/call → injects X-FHIR-Server-URL, X-FHIR-Access-Token, X-Patient-ID
▼
┌─────────────────────────────────────────┐
│ Express API Server │
│ POST /api/mcp │
│ │
│ ┌─────────────────────────────────┐ │
│ │ MCP Streamable HTTP Transport │ │
│ │ (JSON-RPC 2.0 · 2024-11-05) │ │
│ └────────────────┬────────────────┘ │
│ │ │
│ ┌────────────────▼────────────────┐ │
│ │ MCP Tool Router │ │
│ │ fhir_query │ │
│ │ medication_review │ │
│ │ summarize_clinical_notes │ │
│ │ schedule_appointment │ │
│ │ identify_care_gaps │ │
│ └────────────────┬────────────────┘ │
│ │ │
│ ┌────────────────▼────────────────┐ │
│ │ FHIR Client │ │
│ │ Real (Bearer token) ──► EHR │ │
│ │ Mock (no token) ──► Demo │ │
│ └─────────────────────────────────┘ │
└─────────────────────────────────────────┘
Adding to Prompt Opinion
- Go to Configuration → MCP Servers in your Prompt Opinion workspace.
- Paste the MCP Server URL and click Continue.
The platform sends an
initializerequest and reads the server's capabilities. - A FHIR Context toggle appears — enable it.
- Review and authorize the SMART scopes your tools need.
- Done. Every subsequent tool call will carry live FHIR credentials in the headers.
Prompt Opinion FHIR Extension
The server advertises support in every initialize response:
{
"capabilities": {
"extensions": {
"ai.promptopinion/fhir-context": {
"scopes": [
{ "name": "patient/Patient.rs", "required": true },
{ "name": "patient/MedicationRequest.rs", "required": false },
{ "name": "patient/Condition.rs", "required": false },
{ "name": "patient/Observation.rs", "required": false },
{ "name": "patient/DocumentReference.rs", "required": false },
{ "name": "patient/Appointment.crus", "required": false }
]
}
}
}
}
Once authorized, Prompt Opinion injects these headers on every tool call:
| Header | Description |
|---|---|
X-FHIR-Server-URL |
FHIR server base URL — always present |
X-FHIR-Access-Token |
OAuth2 bearer token — present when EHR requires auth |
X-Patient-ID |
Active patient's FHIR ID — absent means system-level context |
X-FHIR-Refresh-Token |
Refresh token — only if offline_access scope granted |
X-FHIR-Refresh-Url |
Token refresh endpoint — only if offline_access scope granted |
When FHIR headers are absent the server falls back to built-in demo data, so tools always return a useful response.
Tool Reference
fhir_query
Raw FHIR R4 resource query for a patient.
{
"resourceType": "MedicationRequest",
"patientId": "patient-001",
"params": { "status": "active" }
}
Supported: Patient · MedicationRequest · Condition · Observation · DocumentReference · Appointment
medication_review
Comprehensive medication safety analysis.
- Drug-drug interaction detection (severity: HIGH / MODERATE / LOW)
- High-risk medications via Beers Criteria
- Duplicate therapeutic class detection
- Missing safety lab flags (e.g. INR monitoring for Warfarin)
- Prioritized clinical recommendations
{
"patientId": "patient-001",
"includeInactive": false
}
Example finding: Mary Johnson — HIGH Warfarin + Aspirin → increased bleeding risk, monitor INR closely.
summarize_clinical_notes
Retrieve and structure FHIR DocumentReference clinical notes.
Extracts: vitals · labs · active diagnoses · current medications · care plan · follow-up items
{
"patientId": "patient-002",
"noteType": "progress",
"maxNotes": 5
}
schedule_appointment
Manage FHIR Appointment resources.
{
"action": "create",
"patientId": "patient-001",
"newAppointment": {
"startDateTime": "2026-06-01T10:00:00",
"durationMinutes": 30,
"serviceType": "Primary Care",
"appointmentType": "FOLLOWUP",
"providerName": "Dr. Sarah Mitchell",
"reason": "Diabetes management follow-up"
}
}
Actions: list · create · cancel
identify_care_gaps
Open quality gap identification aligned with HEDIS, CMS, and USPSTF guidelines.
{
"patientId": "patient-001",
"categories": ["all"]
}
Categories: preventive · chronic_disease · medications · behavioral_health · all
Example output (Mary Johnson): 11 open gaps including overdue HbA1c, missing annual diabetic eye exam, no flu vaccine on record, Warfarin without recent INR documentation.
Demo Patients
Built-in mock data is available at all times without a FHIR server.
| Patient ID | Name | Profile | Clinical Highlight |
|---|---|---|---|
patient-001 |
Mary Johnson | 68F · DM2, HTN, AFib | HIGH Warfarin + Aspirin interaction · 11 care gaps |
patient-002 |
Robert Chen | 52M · DM2, HTN | HbA1c 9.2% (poorly controlled) · overdue labs |
patient-003 |
Sandra Williams | 40F · Depression, Chronic Pain | HIGH Sertraline + Tramadol serotonin syndrome risk |
Quick Test (curl)
# 1. Verify the server is up
curl https://<domain>/api/healthz
# 2. Initialize and confirm the Prompt Opinion extension is declared
curl -X POST https://<domain>/api/mcp \
-H "Content-Type: application/json" \
-H "Accept: application/json, text/event-stream" \
-d '{
"jsonrpc": "2.0", "id": 1, "method": "initialize",
"params": {
"protocolVersion": "2024-11-05",
"capabilities": {},
"clientInfo": { "name": "test", "version": "1.0" }
}
}'
# 3. Run the medication review tool (uses mock data — no FHIR token needed)
curl -X POST https://<domain>/api/mcp \
-H "Content-Type: application/json" \
-H "Accept: application/json, text/event-stream" \
-H "X-Patient-ID: patient-003" \
-d '{
"jsonrpc": "2.0", "id": 2, "method": "tools/call",
"params": {
"name": "medication_review",
"arguments": { "patientId": "patient-003" }
}
}'
Project Structure
artifacts/
├── api-server/ # MCP server (Node 24 · Express 5 · esbuild)
│ └── src/
│ ├── mcp/
│ │ ├── server.ts # Factory + Prompt Opinion extension declaration
│ │ ├── fhir/
│ │ │ ├── client.ts # FHIR HTTP client with mock fallback
│ │ │ └── mock-data.ts # Realistic FHIR R4 demo data
│ │ └── tools/
│ │ ├── fhir-query.ts
│ │ ├── medication-review.ts
│ │ ├── clinical-notes.ts
│ │ ├── appointments.ts
│ │ └── care-gaps.ts
│ └── routes/
│ ├── mcp.ts # Streamable HTTP transport + FHIR header extraction
│ └── health.ts
│
└── healthcare-demo/ # Interactive demo dashboard (React 19 · Vite 7)
└── src/
├── pages/Dashboard.tsx # Patient selector + live tool runner
├── lib/mcp-client.ts # MCP JSON-RPC client
├── App.tsx
└── index.css # Clinical teal/navy theme
Local Development
Requirements: Node.js 24 · pnpm 10+
# Install all workspace dependencies
pnpm install
# Run the MCP API server (proxied to /api by the Replit reverse proxy)
pnpm --filter @workspace/api-server run dev
# Run the demo dashboard (proxied to /)
pnpm --filter @workspace/healthcare-demo run dev
# Full TypeScript check across all packages
pnpm run typecheck
Stack
| Layer | Technology |
|---|---|
| Runtime | Node.js 24 |
| Language | TypeScript 5.9 |
| MCP SDK | @modelcontextprotocol/sdk 1.29 |
| Transport | Streamable HTTP (MCP 2024-11-05) |
| API framework | Express 5 |
| Build | esbuild |
| Frontend | React 19 · Vite 7 · Tailwind CSS 4 |
| Monorepo | pnpm workspaces |
Hackathon
Built for the Prompt Opinion Agents Assemble Challenge — a $25,000 prize pool competition focused on MCP, A2A, and FHIR interoperability in healthcare AI.
- Platform: app.promptopinion.ai
- Docs: docs.promptopinion.ai
- Challenge: Agents Assemble
- Discord: discord.gg/cCBxKpdS7j
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.