Deploy with Docker

Run the MCP server in a Docker container for consistent, reproducible deployments.

Dockerfile

Create a Dockerfile in the project root:

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

# 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:

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):

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:

HEALTHCHECK --interval=30s --timeout=5s \
  CMD curl -f http://localhost:8000/health || exit 1