Agentic AI, a cutting-edge technology, is reshaping the approach of IT professionals towards everyday administration tasks by integrating AI models with software utilities. This integration allows IT admins to execute tasks using natural language instead of traditional tools. Although agentic AI is still evolving and may not cater to all IT operations needs, it does provide value in specific use cases. Let’s delve into how IT teams can leverage agentic AI with Model Context Protocol (MCP) servers to streamline their operations effectively.
Why Use MCP Servers for IT Operations?
MCP serves as a standardized framework that enables IT professionals to connect AI models with software utilities. This framework allows the creation of AI agents, which are software entities capable of autonomously performing actions on a computer system in response to natural-language prompts from human users.
In the MCP framework, an MCP “server” refers to a utility that an AI model can access to execute specific tasks. To create an AI agent, the initial step involves deploying a server that provides the required functionality, such as the ability to execute commands via a specific command-line interface (CLI) tool. Once the server is set up, it is integrated with an AI assistant or model interface, serving as the platform where administrators issue prompts to trigger agentic AI behavior.
Top MCP Servers for IT Operations
1. Filesystem for File Operations
The Filesystem MCP server, developed by the MCP project, enables AI models to interact with local files and directories on a computer or server. IT administrators can utilize this server for tasks like searching for files, renaming files, creating directories, and more. By utilizing Filesystem, IT teams can replace traditional CLI tools and scripts with natural language commands, making file operations more intuitive and accessible.
Related: How AI is Disrupting the Data Center Software Stack
2. MCP Server for MySQL Administration
The MCP Server for MySQL and NodeJS proves beneficial for IT teams handling database administration responsibilities. This server allows AI models to connect to MySQL databases and carry out tasks like data retrieval and database structure modifications without the need for administrators to write SQL code.
While this tool is suitable for basic MySQL administration tasks, it may not be ideal for complex operations or scenarios requiring precise control. Agentic AI lacks transparency in the exact commands it executes to fulfill user requests, which can pose challenges for advanced data management. Nevertheless, for routine tasks, it offers a quicker and simpler alternative to manual SQL query writing.
3. MCP Backup Server for Backup Management
Data backup is a critical IT operation that MCP servers can streamline. The MCP Backup Server enables administrators to create backups using natural language commands, eliminating the necessity for lengthy backup scripts or specialized software.
However, this server does not serve as a comprehensive replacement for traditional backup and recovery systems. It lacks advanced features and primarily focuses on backing up data related to AI development rather than general-purpose backup needs. Nonetheless, it offers a swift and straightforward method to perform basic backups without requiring coding expertise or additional tools.
Related: AI Data Centers: A Popular Term That’s Hard to Define
4. SSH MCP Server for Remote Logins and Administration
SSH, a protocol that facilitates secure remote system logins and command execution, can be challenging for advanced use cases due to its complex syntax. The SSH MCP Server simplifies remote system administration and file management by enabling administrators to utilize SSH without manually running commands. This approach retains SSH’s security while eliminating the need for extensive SSH knowledge.
5. Prometheus MCP Server for IT Monitoring
Various monitoring and observability tools aid IT teams in identifying and resolving performance issues. Traditionally, these tools require administrators to analyze complex visualizations or manually query metrics and logs to interpret performance data. The Prometheus MCP Server offers a simpler alternative by allowing AI models to access metrics collected by Prometheus, a renowned open-source monitoring and observability tool. Similar MCP systems exist for other monitoring tools, showcasing how agentic AI can enhance observability in IT operations.
6. Service Desk Management With Service Desk Plus MCP Server
Service desk and ticketing management are areas where agentic AI offerings remain relatively limited. However, the Service Desk Plus MCP Server provides a notable solution by enabling AI models to interact with ServiceDesk Plus, a service desk platform developed by ManageEngine.
It is essential to note that the official name of this MCP server includes the term “Service Desk Plus,” even though the actual product name is “ServiceDesk Plus.” This MCP server, created by a third-party community contributor rather than ManageEngine, requires thorough security evaluation before integration into service desk environments. For those confident in the underlying code, the server offers a quicker and more efficient approach to managing service requests.
Embracing Agentic AI
Agentic AI signifies a significant transformation in how enterprise IT teams approach their daily tasks. By combining the capabilities of AI models with specialized MCP servers, organizations can streamline operations, reduce technical complexity, and empower team members irrespective of their command-line expertise. While these tools do not substitute the need for skilled IT professionals, they offer a complementary approach that can enhance productivity and accessibility. As the technology advances, we can anticipate even more sophisticated integration between AI and IT operations tools, potentially revolutionizing how teams manage infrastructure, respond to incidents, and deliver services.
