mcp-rubber-duck

[Unit] Description=MCP Rubber Duck with Ollama - Multi-LLM AI Assistant Documentation=https://github.com/nesquikm/mcp-rubber-duck After=docker.service network-online.target Wants=network-online.target Requires=docker.service [Service] Type=forking Restart=always RestartSec=15 TimeoutStartSec=600 TimeoutStopSec=180 # User and group User=pi Group=pi # Working directory (adjust path as needed) WorkingDirectory=/home/pi/mcp-rubber-duck # Environment Environment=COMPOSE_PROJECT_NAME=mcp-rubber-duck Environment=COMPOSE_FILE=docker-compose.yml Environment=COMPOSE_PROFILES=with-ollama # Commands ExecStartPre=/usr/bin/docker compose -f ${COMPOSE_FILE} down ExecStart=/usr/bin/docker compose -f ${COMPOSE_FILE} --profile with-ollama up -d ExecStop=/usr/bin/docker compose -f ${COMPOSE_FILE} down ExecReload=/usr/bin/docker compose -f ${COMPOSE_FILE} --profile with-ollama restart # Health check (wait longer for Ollama to start) ExecStartPost=/bin/sleep 60 ExecStartPost=/bin/sh -c 'docker inspect --format="{{.State.Health.Status}}" mcp-rubber-duck | grep -q healthy || exit 1' # Logging StandardOutput=journal StandardError=journal SyslogIdentifier=mcp-rubber-duck-ollama # Security settings NoNewPrivileges=yes PrivateTmp=yes PrivateDevices=yes ProtectHome=yes ProtectSystem=strict ReadWritePaths=/home/pi/mcp-rubber-duck # Resource limits (higher for Ollama) MemoryMax=2G CPUQuota=300% [Install] WantedBy=multi-user.target