Virtana’s System-Aware MCP Server Can Now Streamline Application Monitoring for End-to-End Enterprise AI Operations 

Virtana is introducing the latest version of its Model Context Protocol (MCP) Server, bringing full-stack enterprise visibility directly to AI agents and LLMs so machines can understand enterprise operations.

Opening the Virtana platform to a broad ecosystem of AI agents, automation systems, and large language models (LLMs), such as OpenAI’s ChatGPT, Anthropic’s Claude, Google Gemini, and Microsoft Copilot, enables AI to execute full-stack decisions across end-to-end enterprise environments, advancing observability from fragmented monitoring into autonomous, self-managing environments, according to the company.

Built on Virtana’s patented full-stack optimization architecture, the platform powers a system dependency graph, a dynamic map that builds a structured understanding of how applications, services, infrastructure, and AI workloads interact across the enterprise.

“The shift to AI-driven operations fundamentally changes what observability must deliver. It is no longer enough to surface signals; platforms must provide a structured understanding of the system itself,” said Amitkumar Rathi, chief product officer at Virtana. “Virtana builds a unified dependency graph that derives operational context across hybrid environments, and the MCP Server exposes that model as a standard interface for AI agents and LLMs. This enables a new operational paradigm where AI systems can analyze, prioritize, and act across the full stack based on real system relationships rather than isolated alerts.” 

Virtana normalizes operational telemetry into a unified system dependency graph—with a dependency-aware representation of distributed applications surfaced through MCP, enabling AI agents powered by leading large language models, including ChatGPT, Claude, and Gemini, to interact directly with structured operational context.

Rather than layering conversational interfaces onto legacy monitoring stacks, Virtana treats natural language as an expression of intent, the company said.

Virtana’s MCP Server translates that intent into structured interactions with the dependency graph, allowing AI agents to retrieve grounded data, analyze relationships, and reason across the full system. 

The Virtana MCP Server enables AI agents to: 

• Query full-stack context in natural language
• Perform autonomous root cause analysis and dependency reasoning
• Analyze system behavior holistically
• Recommend optimizations based on dependency-aware understanding
• Drive automation through open execution frameworks 

With the Virtana MCP Server, AI agents understand enterprise-wide system dependencies, from infrastructure to applications, moving beyond reactive monitoring to deliver intelligent recommendations based on real operational context, the company said. 

For more information about this news, visit www.virtana.com.