# LangCare MCP FHIR Server
[](https://github.com/langcare/langcare-mcp-fhir)
[](https://github.com/langcare/langcare-mcp-fhir/graphs/contributors)
[](https://github.com/langcare/langcare-mcp-fhir/blob/main/LICENSE)
[](https://github.com/langcare/langcare-mcp-fhir/blob/main/go.mod)
Enterprise-grade MCP Server for FHIR-based EMRs. Fully written in Go with enterprise-grade security and 4 generic FHIR operations that work with any FHIR R4 resource type. Supports **EPIC**, **Cerner**, **OpenEMR**, **GCP Healthcare API**, and any generic FHIR R4 server.
Ships with a **[40+ Clinical Skills Library](skills/README.md)** — agent-agnostic workflow guides covering medication management, lab interpretation, clinical decision support, documentation, population health, and more. Extend with ✨ **New: [Claude Managed Agents](cma/README.md)** (9 production-ready clinical AI agents on the Anthropic Managed Agents API), **[MCP Apps](apps/README.md)** (interactive clinical UIs inside Claude Desktop), a **[Healthcare Voice Agent](pipecat-agent/README.md)** (real-time voice AI over FHIR), and a **[LangCare CLI](cli/README.md)** for agent frameworks that don't speak MCP natively.
langcare.ai
## Installation
Install via npm:
```bash
npm install -g @langcare/langcare-mcp-fhir
```
Or use directly without installation:
```bash
npx @langcare/langcare-mcp-fhir -config /path/to/config.yaml
```
## Quick Configuration
LangCare MCP FHIR connects Claude to your FHIR-based EMR system. You need a YAML configuration file pointing to your backend.
### 1. Get a Config Template
Choose your backend:
- **EPIC:** [config.epic.example.yaml](https://github.com/langcare/langcare-mcp-fhir/blob/main/configs/config.epic.example.yaml)
- **Cerner:** [config.cerner.example.yaml](https://github.com/langcare/langcare-mcp-fhir/blob/main/configs/config.cerner.example.yaml)
- **OpenEMR:** [config.openemr.example.yaml](https://github.com/langcare/langcare-mcp-fhir/blob/main/configs/config.openemr.example.yaml)
- **GCP Healthcare API:** [config.gcp.example.yaml](https://github.com/langcare/langcare-mcp-fhir/blob/main/configs/config.gcp.example.yaml)
- **Any FHIR R4 Server:** [config.base.example.yaml](https://github.com/langcare/langcare-mcp-fhir/blob/main/configs/config.base.example.yaml)
### 2. Configure Claude Desktop
Add to your Claude Desktop config file (`~/.config/Claude/claude_desktop_config.json`):
```json
{
"mcpServers": {
"langcare-mcp-fhir": {
"command": "langcare-mcp-fhir",
"args": ["-config", "/path/to/your/config.yaml"]
}
}
}
```
On macOS, the config is typically at:
```
~/Library/Application\ Support/Claude/claude_desktop_config.json
```
### 3. Restart Claude Desktop
Close and reopen Claude Desktop. The FHIR tools will now be available.
**Need detailed setup help?** See the [Local Testing Guide](https://github.com/langcare/langcare-mcp-fhir/blob/main/docs/LOCAL-TESTING.md).
## Architecture
This MCP server acts as an intelligent proxy between AI agents and FHIR R4 servers. It exposes 4 generic FHIR operations through the Model Context Protocol (MCP), enabling AI-powered workflows for any FHIR resource type.
**Key Design:**
- **MCP SDK:** Official `github.com/modelcontextprotocol/go-sdk` (Anthropic/Google maintained)
- **FHIR Client:** Generic HTTP client working with any FHIR R4 server
- **Transport:** stdio and Streamable HTTP
- **Backend:** Proxy to existing FHIR server (no database)
- **Language:** 100% Go for high performance and reliability
## 4 Generic MCP Tools
All tools work with **any FHIR resource type** (Patient, Observation, Medication, etc.):
### 1. fhir_read
Read a FHIR resource by type and ID.
```json
{
"resourceType": "Patient",
"id": "example-123"
}
```
### 2. fhir_search
Search FHIR resources with query parameters.
```json
{
"resourceType": "Patient",
"queryParams": "name=John&birthdate=gt1990-01-01"
}
```
### 3. fhir_create
Create a new FHIR resource.
```json
{
"resourceType": "Observation",
"resource": {
"resourceType": "Observation",
"status": "final",
"code": { ... },
"subject": { "reference": "Patient/123" }
}
}
```
### 4. fhir_update
Update an existing FHIR resource.
```json
{
"resourceType": "Patient",
"id": "example-123",
"resource": {
"resourceType": "Patient",
"id": "example-123",
"name": [{ "family": "Smith" }]
}
}
```
## Security Architecture
LangCare MCP FHIR implements a **two-layer security model** for HIPAA-compliant healthcare data access:
```
┌─────────────┐ ┌──────────────┐ ┌─────────────┐
│ Claude │ Auth1 │ MCP Server │ Auth2 │ FHIR API │
│ Client │────────▶│ (Go) │────────▶│ (EMR) │
└─────────────┘ └──────────────┘ └─────────────┘
Auth1: MCP Client Authentication (Bearer Token/API Key)
Auth2: FHIR Backend Authentication (Bearer/OAuth2/SMART on FHIR)
```
### Security Features
- ✅ **TLS 1.3** encryption for HTTP transport
- ✅ **PHI Scrubbing** in logs (enabled by default)
- ✅ **HIPAA-compliant** audit logging
- ✅ **No persistent PHI storage** (stateless proxy)
- ✅ **Secrets via environment variables** (never in config files)
- ✅ **OAuth 2.0** with automatic token refresh
- ✅ **mTLS** support for service-to-service communication
- ✅ **Rate limiting** per client
### Supported Authentication Methods
- **Bearer Token** - Simple API key authentication
- **OAuth2** - Full OAuth2 flow with token refresh
- **SMART on FHIR Backend Services** - `private_key_jwt` (RS384) for EPIC, OpenEMR, and other SMART-conformant EMRs
- **SMART on FHIR** - EPIC, Cerner, OpenEMR, and other EMR standards
- **Basic Auth** - Username/password authentication
- **Custom** - Extensible for additional auth methods
**For complete security documentation, see [Security Guide](https://github.com/langcare/langcare-mcp-fhir/blob/main/docs/SECURITY.md):**
- HIPAA compliance checklist
- OAuth configuration for EPIC/Cerner/GCP
- Kubernetes security manifests
- Credential management procedures
- Audit logging implementation
## MCP Apps (Interactive UIs)
LangCare MCP FHIR ships with built-in **MCP Apps** — interactive, rich UI views that run directly inside MCP-capable hosts like Claude Desktop. Unlike traditional chat-based tool output, MCP Apps render full React-based interfaces with charts, tables, and interactive controls while using the same underlying FHIR tools.
**How it works:** Each app is a single-file HTML bundle (React + TypeScript, compiled with Vite) that gets embedded into the Go binary at compile time via `go:embed`. At runtime the MCP server registers each app as both an MCP Resource (`text/html;profile=mcp-app`) and a dedicated MCP Tool linked via `_meta.ui.resourceUri`. When an MCP host calls the tool, it fetches the resource and renders the UI. The app calls back into the server's generic FHIR tools (`fhir_search`, `fhir_read`, etc.) through `app.callServerTool()` — no LLM round-trips for data fetching.
**Advantages over plain tool output:**
- **Rich visualization** — SVG charts, color-coded cards, expandable detail panels
- **Interactive controls** — search fields, date range pickers, click-to-expand rows
- **Deterministic data fetching** — apps call FHIR tools directly, no LLM involvement in data retrieval
- **Zero external dependencies** — everything inlines into a single HTML file, embedded in the binary
- **Works offline** — no CDN, no external scripts, no network requests beyond FHIR API calls
### Built-in Apps
| App | Tool | Description |
|-----|------|-------------|
| **FHIR Explorer** | `fhir_explorer` | Interactive FHIR resource browser. Search, read, create, and update any FHIR R4 resource type with JSON detail views. |
| **Patient Chart Review** | `patient_chart_review` | Clinical dashboard with patient demographics, active conditions, medications, vitals, labs, and vitals trend charts (BP + weight over time). |
Both apps are reference implementations demonstrating the MCP Apps pattern. See **[apps/README.md](apps/README.md)** for architecture details and how to build new apps.
Patient Chart Review running inside Claude Desktop
## Agent Usage
AI agents use LangCare MCP FHIR Server to help healthcare professionals access and manage patient health records through 4 FHIR tools. The server handles EMR authentication, allowing agents to focus on clinical workflows while maintaining strict privacy and accuracy standards.
**Agent capabilities:**
- **Search, Read, Create, Update** - Any FHIR R4 resource (Patient, Observation, Medication, etc.)
- **Patient privacy** - Use partial identifiers, confirm identity before updates
- **Clinical accuracy** - Verify data, use standard codes (LOINC, SNOMED, RxNorm)
- **Professional communication** - Structure responses with context, findings, and next steps
**Common workflows:**
- **Patient lookup:** Search by name/DOB → verify identity → read full details
- **Clinical review:** Retrieve labs, vitals, medications → present with reference ranges
- **Documentation:** Extract structured data → map to FHIR resources → confirm → create
- **Updates:** Verify existing resource → modify → confirm changes → update
**System support:**
- Works with any FHIR R4 resource type (60+ types including DocumentReference, Binary, Media)
- Automatic authentication and token refresh to EPIC, Cerner, OpenEMR, GCP Healthcare API
- HIPAA-compliant PHI handling with audit logging
- Comprehensive OAuth2 scopes for clinical data access
**📖 Complete guide:** [Agent Prompt Guide](https://github.com/langcare/langcare-mcp-fhir/blob/main/docs/AGENT_PROMPT.md) - System prompt, tool examples, workflows, and error handling
## Clinical Skills Library (Optional)
**40+ agent-agnostic clinical workflow guides** that teach AI agents how to perform complex healthcare tasks using the MCP server's 4 FHIR tools (`fhir_search`, `fhir_read`, `fhir_create`, `fhir_update`).
- **Optional** - The MCP server works without them
- **Portable** - Work with Claude, ChatGPT, Gemini, or any AI agent
- **Evidence-based** - Built on USPSTF, ADA, ACC/AHA, CDC, ACOG, KDIGO, and other society guidelines
- **Copy-paste ready** - Add a skill's `SKILL.md` to your agent's system prompt or custom instructions
### Skill Categories (40 Skills)
| Category | Skills | Examples |
|----------|--------|----------|
| **Patient Data & Summary** | 5 | Demographics, clinical summary (CCD-style), problem list audit, allergy review, insurance coverage |
| **Medication Management** | 5 | Med reconciliation, drug interactions (CYP450), adherence (MPR/PDC), Beers Criteria, opioid risk (ORT/MME) |
| **Lab & Diagnostics** | 5 | Lab interpretation, critical values (CAP/CLIA), pre-op labs, diabetes panel (ADA), renal function (KDIGO) |
| **Clinical Decision Support** | 5 | Sepsis (qSOFA/SOFA), cardiovascular risk (ASCVD/HEART), VTE (Wells/Caprini), fall risk (Morse), pneumonia (CURB-65) |
| **Care Coordination** | 5 | Discharge planning (LACE), referrals, care gaps (USPSTF), transitions of care (I-PASS), follow-up tasks |
| **Documentation** | 5 | SOAP notes, H&P, progress notes, discharge summaries, procedure notes |
| **Population Health** | 5 | Panel overview, quality measures (HEDIS), chronic disease registries, immunization status (CDC), preventive care compliance |
| **Specialty** | 5 | Prenatal (ACOG), pediatric growth (WHO/CDC), mental health (PHQ-9/GAD-7), oncology (TNM/RECIST), chronic pain |
**Full catalog with links:** [skills/README.md](skills/README.md)
### How to Use Skills
1. **Browse** the [skills/core/](skills/core/) directory and pick a skill
2. **Copy** the skill's `SKILL.md` content into your AI agent's system prompt or custom instructions
3. **Reference files** in each skill's `references/` subdirectory contain detailed clinical knowledge (scoring criteria, code tables, thresholds) that can optionally be included for deeper clinical accuracy
```
# Example: Add medication-reconciliation skill to your agent
skills/core/medication-management/medication-reconciliation/
├── SKILL.md # Copy this into agent instructions
└── references/
├── reconciliation-process.md # Joint Commission standards
└── high-risk-medications.md # ISMP high-alert drug list
```
**Integration guides:** [Claude](integrations/claude/) | [ChatGPT](integrations/chatgpt/) | [Gemini](integrations/gemini/)
**Community contributions welcome** - see [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines.
## Development & Testing
### Build from Source
```bash
make build
```
### Run Locally (stdio mode)
```bash
make run
# or
./bin/langcare-mcp-fhir -config configs/config.local.yaml
```
### Run in HTTP Mode (Streamable HTTP)
```bash
make run-http
# or
./bin/langcare-mcp-fhir -http -port 8080 -config configs/config.yaml
```
Starts the server with Streamable HTTP transport on `/mcp` and health check on `/health`.
### Run Tests
```bash
make test
```
### Lint Code
```bash
make lint
```
### Deploy to Fly.io (Remote Streamable HTTP)
Deploy as a remote MCP server with Streamable HTTP transport, accessible by any MCP-compatible AI agent from anywhere.
```bash
# Install Fly CLI
brew install flyctl
fly auth login
# Create app
fly apps create --name langcare-mcp-dev
# Set CONFIG_FILE in fly/fly.dev.toml [env] block for your provider (EPIC or GCP)
# Then set secrets (EPIC example):
fly secrets set \
EPIC_BASE_URL="https://fhir.epic.com/interconnect-fhir-oauth/api/FHIR/R4" \
EPIC_CLIENT_ID="your-client-id" \
EPIC_TOKEN_URL="https://fhir.epic.com/interconnect-fhir-oauth/oauth2/token" \
EPIC_PRIVATE_KEY_B64="$(base64 < keys/epic/private-key.pem)" \
MCP_AUTH_TOKENS="your-token" \
--app langcare-mcp-dev
# Deploy
fly deploy -c fly/fly.dev.toml --app langcare-mcp-dev
# Verify
curl https://langcare-mcp-dev.fly.dev/health
```
Connect any MCP client to:
```
URL: https://langcare-mcp-dev.fly.dev/mcp
Auth: Authorization: Bearer your-token
```
Claude Desktop (`claude_desktop_config.json`):
```json
{
"mcpServers": {
"langcare-fhir": {
"url": "https://langcare-mcp-dev.fly.dev/mcp",
"headers": {
"Authorization": "Bearer your-token"
}
}
}
}
```
Supports EPIC and GCP Healthcare API providers. See **[fly/README.md](fly/README.md)** for provider setup, secrets, and full deployment guide.
### Local Testing with EPIC
For step-by-step instructions on setting up EPIC credentials and testing locally:
**[📖 Local Testing Guide](https://github.com/langcare/langcare-mcp-fhir/blob/main/docs/LOCAL-TESTING.md)**
This guide covers:
- Generating RSA keys and JWKS
- Configuring EPIC credentials
- Running the server locally
- Testing with Claude Desktop
- Troubleshooting common issues
**Quick credential test:**
```bash
# Test your EPIC credentials before running the server
go run test/test_epic_token.go "your-client-id" "/path/to/private-key.pem"
```
## Project Structure
```
langcare-mcp-fhir/
├── cmd/
│ └── server/
│ └── main.go # Entry point
├── internal/
│ ├── apps/ # MCP Apps (embedded UIs)
│ │ ├── embed.go # go:embed directive for HTML bundles
│ │ ├── registry.go # App metadata, tool names, resource URIs
│ │ └── dist/ # Built HTML bundles (copied by build)
│ │ ├── fhir-explorer.html # FHIR Explorer single-file bundle
│ │ └── patient-chart-review.html # Patient Chart Review single-file bundle
│ ├── audit/
│ │ └── logger.go # HIPAA audit logging
│ ├── config/
│ │ └── config.go # YAML configuration loading
│ ├── fhir/
│ │ ├── client.go # FHIR HTTP client interface
│ │ ├── types.go # FHIR client types
│ │ └── providers/ # Backend implementations
│ │ ├── base.go # Base HTTP provider
│ │ ├── epic.go # EPIC OAuth2 provider
│ │ ├── cerner.go # Cerner OAuth2 provider
│ │ ├── openemr.go # OpenEMR SMART Backend Services provider
│ │ └── gcp.go # GCP Healthcare API provider
│ ├── mcp/
│ │ └── server.go # MCP server + app registration
│ ├── middleware/
│ │ ├── auth.go # MCP authentication
│ │ └── rate_limit.go # Rate limiting
│ ├── tools/ # MCP tool implementations
│ │ ├── registry.go # Tool registry
│ │ ├── fhir_read.go # Read FHIR resource
│ │ ├── fhir_search.go # Search FHIR resources
│ │ ├── fhir_create.go # Create FHIR resource
│ │ └── fhir_update.go # Update FHIR resource
│ └── transport/
│ ├── stdio.go # stdio transport (Claude Desktop)
│ └── http.go # Streamable HTTP transport (production)
├── apps/ # MCP App source code (React + TypeScript)
│ ├── README.md # App development guide
│ ├── package.json # Shared dependencies (React 19, MCP Apps SDK)
│ ├── vite.config.ts # Vite build config (single-file output)
│ ├── tsconfig.json # TypeScript config
│ ├── fhir-explorer/ # FHIR Explorer app
│ │ ├── index.html
│ │ └── src/
│ │ ├── app.tsx
│ │ └── global.css
│ └── patient-chart-review/ # Patient Chart Review app
│ ├── index.html
│ └── src/
│ ├── app.tsx
│ └── global.css
├── scripts/
│ ├── build-apps.sh # Build all apps → internal/apps/dist/
│ ├── create_jwks.sh # Generate JWKS from public key (EPIC)
│ └── create_jwks_openemr.sh # Generate JWKS from public key (OpenEMR)
├── pkg/
│ └── types/
│ └── errors.go # Custom error types
├── configs/
│ ├── config.epic.example.yaml # Example configuration for EPIC
│ ├── config.cerner.example.yaml # Example configuration for Cerner
│ ├── config.openemr.example.yaml # Example configuration for OpenEMR
│ ├── config.gcp.example.yaml # Example configuration for GCP
│ └── config.base.example.yaml # Example configuration for any FHIR R4 server
├── docs/
│ ├── AGENT_PROMPT.md # AI agent system prompt
│ ├── EPIC-APP-SECURITY.md # EPIC authentication setup
│ ├── OPENEMR-APP-SECURITY.md # OpenEMR SMART Backend Services setup
│ ├── EPIC-SCOPES.md # OAuth2 scopes reference
│ ├── LOCAL-TESTING.md # Local development guide
│ └── SECURITY.md # Production security guide
├── test/
│ ├── README.md # Test documentation
│ └── test_epic_token.go # EPIC OAuth2 token tester
├── fly/
│ ├── Dockerfile # Multi-stage Go build for Fly.io
│ ├── docker-entrypoint.sh # Key materialization + server startup
│ ├── fly.dev.toml # Fly.io dev deployment config
│ ├── config.fly.epic.yaml # Fly.io EPIC provider config
│ ├── config.fly.gcp.yaml # Fly.io GCP provider config
│ └── README.md # Fly.io deployment guide
├── bin/ # Build output (gitignored)
│ └── langcare-mcp-fhir # Compiled binary
├── go.mod # Go module definition
├── go.sum # Go module checksums
├── Makefile # Build commands
└── README.md # This file
```
**Note:** The following are gitignored and not committed:
- `keys/` - Private keys and credentials
- `config.local.*.yaml` - Local configuration files
- `bin/` - Compiled binaries
- `.env` - Environment variables
- `apps/node_modules/`, `apps/dist/`, `apps/dist-tmp/` - App build artifacts
## Healthcare Voice Agent
Real-time voice AI that lets patients ask about their health records and get spoken answers pulled directly from their EMR.
**The stack:** [PipeCat](https://docs.pipecat.ai/) (open-source, Daily.co) for the voice pipeline — STT, LLM orchestration, TTS with sub-3-second latency. Claude for clinical reasoning and tool calling. LangCare MCP FHIR Server (open-source, Go) as a stateless proxy to any FHIR R4 EMR — Epic, Cerner, GCP Healthcare API.
**MCP is the glue.** PipeCat's native MCP client auto-discovers FHIR tools at startup. Patient asks "What medications am I on?" — Claude calls `fhir_search` — PipeCat routes it to the MCP server — data comes back — Claude responds in natural speech. No manual tool schemas needed.
**Three-layer HIPAA auth:** Caller identity verified before the session starts, bearer token to MCP, OAuth2/SMART on FHIR to EMR. Zero PHI storage.
**Everything is swappable.** Replace Claude with Gemini, DeepGram with Google STT, Daily with WebSocket. The MCP FHIR layer and clinical prompts stay the same.
**[Full documentation and setup guide](pipecat-agent/README.md)**
## LangCare CLI
Command-line interface that wraps the 4 FHIR MCP tools (`fhir_search`, `fhir_read`, `fhir_create`, `fhir_update`) as CLI subcommands over HTTP. Built for AI agent frameworks that don't speak MCP natively — LangChain, smolagents, CrewAI, AutoGen, and any framework that can call a subprocess. The CLI handles the MCP session handshake internally, so agents get clean JSON on stdout with no protocol knowledge required.
```bash
# Install
pip install "langcare-cli @ git+https://github.com/langcare/langcare-mcp-fhir.git#subdirectory=cli"
# Use
langcare fhir search Patient --query "name=John"
langcare fhir read Patient 123
langcare fhir create Observation --data @obs.json
langcare fhir update Patient 123 --data @patient.json
```
The 40+ clinical skills in the [Skills Library](skills/README.md) work as-is — skills reference abstract tool names, not transport. Register the CLI as subprocess tools in your agent framework and skills run without modification.
**[Full documentation and setup guide](cli/README.md)**
## Documentation
### Getting Started
- **[📖 Local Development & Testing Guide](https://github.com/langcare/langcare-mcp-fhir/blob/main/docs/LOCAL-TESTING.md)** - Complete guide for local setup and testing
- **[🚀 Installation & Configuration](#installation)** - Quick setup guide above
### Agent Integration
- **[🤖 Agent Prompt Guide](https://github.com/langcare/langcare-mcp-fhir/blob/main/docs/AGENT_PROMPT.md)** - Complete guide for AI agents using LangCare MCP FHIR (tool examples, workflows, best practices)
### Security & Authentication
- **[🛡️ Security Documentation](https://github.com/langcare/langcare-mcp-fhir/blob/main/docs/SECURITY.md)** - Complete security architecture and HIPAA compliance
- **[🔐 EPIC Setup Guide](https://github.com/langcare/langcare-mcp-fhir/blob/main/docs/EPIC-APP-SECURITY.md)** - JWT authentication, key generation, and JWKS registration
- **[🔐 OpenEMR Setup Guide](https://github.com/langcare/langcare-mcp-fhir/blob/main/docs/OPENEMR-APP-SECURITY.md)** - SMART on FHIR Backend Services (`private_key_jwt`/RS384) setup, JWKS generation, and OpenEMR API client registration
- **[📋 EPIC Scopes Reference](https://github.com/langcare/langcare-mcp-fhir/blob/main/docs/EPIC-SCOPES.md)** - Complete OAuth2 scopes guide for FHIR resources
- **[🔑 Authentication Methods](#supported-authentication-methods)** - Supported auth methods
### Deployment
- **[Fly.io Deployment Guide](https://github.com/langcare/langcare-mcp-fhir/blob/main/docs/FLY-DEPLOYMENT.md)** - Remote Streamable HTTP deployment, provider configs, secrets, Docker
### Development & Testing
- **[🧪 Testing Methods](https://github.com/langcare/langcare-mcp-fhir/blob/main/docs/LOCAL-TESTING.md#testing-with-claude-desktop)** - Claude Desktop, MCP Inspector, manual testing, and automation
- **[📦 Project Structure](#project-structure)** - Directory layout and architecture
- **[🔧 Build Commands](#development--testing)** - Development workflow
## Dependencies
- `github.com/modelcontextprotocol/go-sdk` - Official MCP SDK
- `gopkg.in/yaml.v3` - Configuration parsing
- `golang.org/x/oauth2` - OAuth2 client library
- `github.com/golang-jwt/jwt/v5` - JWT signing and verification
- Go 1.25+
## HIPAA Compliance
- PHI scrubbing enabled by default
- Never logs patient identifiers
- TLS support for HTTP transport
- Proper error sanitization
- Audit logging ready
- Stateless proxy design (no persistent storage)
## Testing
### Public Test Server
Default configuration uses HAPI FHIR public test server (`https://hapi.fhir.org/baseR4`) for immediate testing without setup.
### Test Your Setup
- **[📖 Local Development & Testing Guide](https://github.com/langcare/langcare-mcp-fhir/blob/main/docs/LOCAL-TESTING.md)** - Complete guide for setup, testing with Claude Desktop, MCP Inspector, and automation
- **[🔐 EPIC Security Setup](https://github.com/langcare/langcare-mcp-fhir/blob/main/docs/EPIC-APP-SECURITY.md)** - Detailed EPIC authentication guide
- **[🛡️ Security Documentation](https://github.com/langcare/langcare-mcp-fhir/blob/main/docs/SECURITY.md)** - Production deployment and security
## Claude Managed Agents
9 production-ready clinical AI agents built on the **[Anthropic Managed Agents API](https://docs.anthropic.com/)**. Each agent connects to a LangCare MCP FHIR Server and uses a curated set of domain-specific clinical skills drawn from the [40+ Clinical Skills Library](skills/README.md). Sessions are persistent, visible at **[platform.claude.com/workspaces/default/sessions](https://platform.claude.com/workspaces/default/sessions)**, and can be run interactively or driven by a single prompt.
| Agent | Domain |
|-------|--------|
| **Medication Management** | Reconciliation, drug interactions, Beers Criteria, opioid risk, adherence |
| **Care Coordination** | Discharge planning, referrals, care gaps, transitions of care, follow-up tasks |
| **Clinical Decision Support** | Sepsis qSOFA, cardiovascular risk, VTE, fall risk, CURB-65 |
| **Clinical Triage** | Clinical summary, acuity, vitals review, sepsis indicators |
| **Documentation** | SOAP notes, H&P, progress notes, discharge summaries, procedure notes |
| **Lab & Diagnostics** | Critical values, diabetes panel, lab interpretation, pre-op labs, renal function |
| **Patient Data** | Demographics, allergy review, clinical summary, insurance coverage, problem list |
| **Population Health** | Chronic disease registries, immunization status, preventive care, quality measures |
| **Specialty Care** | Chronic pain, mental health, oncology, pediatric growth, prenatal |
### Quickstart
```bash
# 1. Set environment variables
export ANTHROPIC_API_KEY=sk-ant-...
export LANGCARE_MCP_URL=https://langcare-mcp-dev.fly.dev/mcp
export LANGCARE_MCP_TOKEN=your-bearer-token
# 2. Upload skills, create environment + vault, deploy all 9 agents
cd cma/scripts
./setup.sh dev
# 3. Run a session
./run-session.sh "Show active medications for patient ID d886a934-5568-42b3-9324-0f0b05fc018c"
```
`setup.sh` is idempotent — safe to re-run. At the end it prints the Environment ID and Vault ID needed for sessions.
**Full guide:** [cma/README.md](cma/README.md) — env vars, all scripts reference, troubleshooting.
---
## Contributing
**We welcome contributions from healthcare professionals, developers, and informaticists!**
There are three main ways to contribute:
### 1. Core MCP Server (Go Development)
- Bug fixes and performance improvements
- New FHIR provider implementations (AllScripts, Athenahealth, etc.)
- Security enhancements and observability features
- Testing and CI/CD improvements
### 2. Clinical Skills (Healthcare Workflows)
- Evidence-based clinical workflows using FHIR
- Specialty-specific protocols (cardiology, oncology, etc.)
- Population health and quality measure workflows
- Clinical decision support algorithms
Skills are agent-agnostic workflow guides that work across Claude, ChatGPT, and Gemini. No coding required - just clinical expertise and FHIR knowledge!
### 3. MCP Apps (Interactive UIs)
- New clinical or administrative UI apps
- Enhancements to existing apps (FHIR Explorer, Patient Chart Review)
- Reusable components and patterns for healthcare UIs
See **[apps/README.md](apps/README.md)** for the development guide.
### 4. Agent Integrations (Platform Setup)
- Setup guides for new AI platforms
- Deployment examples (Docker, Kubernetes, cloud)
- Monitoring and observability setups
- CI/CD pipelines
**Get started:** Read [CONTRIBUTING.md](https://github.com/langcare/langcare-mcp-fhir/blob/main/CONTRIBUTING.md) for detailed guidelines, code standards, and submission process.
**Recognition:** Contributors are credited in README, release notes, and skill/integration author credits. Outstanding contributors may be invited as maintainers.
**Questions?** Open a [GitHub Discussion](https://github.com/langcare/langcare-mcp-fhir/discussions) or [issue](https://github.com/langcare/langcare-mcp-fhir/issues)!
## Community
- **GitHub Discussions** - Ask questions, share ideas: https://github.com/langcare/langcare-mcp-fhir/discussions
- **GitHub Issues** - Report bugs, request features: https://github.com/langcare/langcare-mcp-fhir/issues
- **Contributing Guide** - How to contribute: https://github.com/langcare/langcare-mcp-fhir/blob/main/CONTRIBUTING.md
- **Skills** - Clinical workflows: https://github.com/langcare/langcare-mcp-fhir/blob/main/skills/README.md
## License
See [LICENSE](https://github.com/langcare/langcare-mcp-fhir/blob/main/LICENSE) file.
---
**Built with ❤️ by the LangCare team and contributors.**
*Improving healthcare through better AI infrastructure.*