# Deploy with Docker
Run the MCP server in a Docker container for consistent, reproducible deployments.
## Dockerfile
Create a `Dockerfile` in the project root:
```dockerfile
FROM python:3.12-slim
WORKDIR /app
COPY pyproject.toml .
COPY src/ src/
RUN pip install --no-cache-dir .
EXPOSE 8000
# Default: stdio transport (for MCP clients)
CMD ["epsteinexposed-mcp"]
```
## Build & Run
```bash
# Build the image
docker build -t epsteinexposed-mcp .
# Run with stdio transport (pipe to MCP client)
docker run -i epsteinexposed-mcp
# Run with SSE transport (for HTTP-based clients)
docker run -p 8000:8000 epsteinexposed-mcp \
python -c "from src.server import mcp; mcp.run(transport='sse', host='0.0.0.0', port=8000)"
```
## Environment Variables
Pass environment variables at runtime:
```bash
docker run -e EPSTEIN_API_BASE_URL=https://custom-api.example.com/api \
-i epsteinexposed-mcp
```
## Docker Compose
If you're running this alongside other services (e.g., the LinkedStein backend):
```yaml
services:
epstein-mcp:
build: ./epsteinexposed-mcp
environment:
- EPSTEIN_API_BASE_URL=https://epsteinexposed.com/api
stdin_open: true
tty: true
```
## Health Check
For SSE transport deployments, add a health check:
```dockerfile
HEALTHCHECK --interval=30s --timeout=5s \
CMD curl -f http://localhost:8000/health || exit 1
```
