Global MCP Server

# Docker Compose configuration for Global MCP Server # Supports both development and production deployments version: "3.8" services: globalmcp: build: context: . target: development # Use 'production' for production builds container_name: globalmcp-server ports: - "8000:8000" volumes: # Development: Mount source code for hot reload - .:/app # Share Ollama models between host and container - ~/.ollama:/home/mcpuser/.ollama # Persist MCP configuration - ./.vscode:/app/.vscode - ./config:/app/config environment: - MCP_SERVER_HOST=0.0.0.0 - MCP_SERVER_PORT=8000 - PYTHONPATH=/app # Optional: Set log level - LOG_LEVEL=INFO networks: - mcp-network depends_on: - ollama restart: unless-stopped # Resource limits (adjust based on your needs) deploy: resources: limits: memory: 1G cpus: "0.5" reservations: memory: 512M cpus: "0.25" ollama: image: ollama/ollama:latest container_name: ollama-server ports: - "11434:11434" volumes: # Persist Ollama models - ollama_data:/root/.ollama environment: - OLLAMA_HOST=0.0.0.0 networks: - mcp-network restart: unless-stopped # GPU support (uncomment if you have NVIDIA GPU) # deploy: # resources: # reservations: # devices: # - driver: nvidia # count: 1 # capabilities: [gpu] # Optional: Redis for caching (uncomment if needed) # redis: # image: redis:7-alpine # container_name: redis-cache # ports: # - "6379:6379" # volumes: # - redis_data:/data # networks: # - mcp-network # restart: unless-stopped networks: mcp-network: driver: bridge name: mcp-network volumes: ollama_data: name: ollama_models # redis_data: # name: redis_cache