version: '3.8'
services:
crawl4ai-mcp-server:
build:
context: .
dockerfile: Dockerfile
container_name: crawl4ai-mcp-server
restart: unless-stopped
environment:
# MCP Server Configuration
- FASTMCP_LOG_LEVEL=INFO
- PYTHONPATH=/app
- PYTHONUNBUFFERED=1
# Optional: Set transport mode (default is STDIO)
# - MCP_TRANSPORT=http
# - MCP_HOST=0.0.0.0
# - MCP_PORT=8000
# Optional: LLM API Keys (uncomment and set if needed)
# - OPENAI_API_KEY=${OPENAI_API_KEY}
# - ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}
# - AZURE_OPENAI_API_KEY=${AZURE_OPENAI_API_KEY}
# - AZURE_OPENAI_ENDPOINT=${AZURE_OPENAI_ENDPOINT}
# File processing limits
- MAX_FILE_SIZE_MB=100
# Performance tuning
- MAX_CONCURRENT_REQUESTS=5
- CACHE_TTL=900 # 15 minutes
# No ports exposed to localhost - only accessible via shared_net
expose:
- "8000" # HTTP transport port (if enabled)
volumes:
# Optional: Mount for persistent cache
- crawl4ai_cache:/app/cache
# Optional: Mount for logs
- crawl4ai_logs:/app/logs
# Optional: Mount configuration directory
- ./config:/app/config:ro
networks:
- shared_net
# Security context
user: "1000:1000"
# Resource limits
deploy:
resources:
limits:
memory: 2G
cpus: '1.0'
reservations:
memory: 512M
cpus: '0.5'
# Health check
healthcheck:
test: ["CMD", "python", "-c", "import asyncio; from crawl4ai_mcp.server import mcp; print('Health check passed')"]
interval: 30s
timeout: 10s
retries: 3
start_period: 60s
networks:
shared_net:
external: true
volumes:
crawl4ai_cache:
driver: local
crawl4ai_logs:
driver: local
