MCP Server for Managing and Executing n8n Workflows

This workflow is designed to automate the deployment and management of Docker-based Immich service instances, supporting operations such as starting, stopping, mounting, setting permissions, and retrieving logs for containers. Through API interfaces and SSH remote execution, users can flexibly manage the container lifecycle and achieve one-stop status monitoring and user management. Additionally, the built-in nginx proxy configuration feature ensures stable operation of the service in a reverse proxy environment, making it suitable for cloud service providers, system operations personnel, and enterprise IT teams, thereby enhancing operational efficiency and service delivery quality.

This workflow automatically receives status update requests via Webhook, intelligently synchronizing the archiving status of Clockify projects. Depending on whether the task is resolved, it automatically toggles the Clockify project between "archived" and "active," effectively addressing the cumbersome and error-prone nature of manual operations. It is suitable for teams that need to maintain consistency between task status and time tracking tools, significantly enhancing the efficiency and accuracy of project management, and ensuring that the project status is always in sync with the actual tasks.

This workflow enables real-time monitoring of error events in the automated system. Once an error occurs, a detailed notification is immediately sent via Mattermost, and Twilio SMS alerts are utilized to ensure that relevant personnel are quickly informed of the anomaly. This multi-channel notification mechanism effectively prevents business interruptions or data loss due to undetected issues, enhancing operational efficiency and response speed. It is suitable for teams and enterprises that require real-time monitoring of business processes.

This workflow intelligently and automatically assigns unassigned tasks that have been pending for more than 5 days by integrating JIRA, OpenAI, and the Supabase vector database. It utilizes AI technology to retrieve similar resolved issues, identify the best team members, and take into account the current task load, ensuring that tasks are assigned efficiently and accurately, while avoiding omissions and resource waste. It is suitable for agile development and project management, significantly reducing the manual allocation workload and enhancing team collaboration and management efficiency.

This workflow uses the AMQP Trigger node to listen for and receive messages from the ActiveMQ message queue in real-time, ensuring immediate capture and processing of messages. It effectively addresses the efficiency issue of retrieving messages from the ActiveMQ queue, avoiding manual polling or delayed responses, making it suitable for scenarios that require real-time message processing, such as order notifications and system event triggers. This workflow provides developers and operations personnel with tools to enhance message processing efficiency and supports the construction of automated processes.

This workflow implements automatic version detection and updates for running Docker containers. It regularly checks the differences between the current version and the latest released version on GitHub, automatically notifying users if updates are available. Upon user confirmation, it pulls the latest image and restarts the container. Notifications and interactions are conducted via Telegram, allowing users to conveniently manage updates remotely, ensuring that the platform always runs on the latest stable version, thereby enhancing system security and functional integrity.

This workflow implements automatic backups of workflow configuration files, categorically storing them by year and month in a designated GitHub repository, with files named using a unique ID. It supports scheduled or manual triggers and intelligently identifies file statuses to optimize backup efficiency. After the backup is complete, it automatically sends a Slack notification to ensure users are promptly informed of the backup status. This process is suitable for enterprises and teams, reducing manual intervention and management costs while effectively ensuring the security and stability of the workflow.

This workflow implements an automatic message cleanup feature for Discord channels. It scans all channels of a specified server at scheduled intervals each day, automatically deleting messages that are older than seven days to keep the channels tidy. By appropriately setting wait times, it effectively avoids API call rate limits, ensuring the smooth execution of tasks and reducing the risk of being banned. This significantly alleviates the burden of manual management for community operators and business users, enhancing channel activity and information security.