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Mirantis, a Kubernetes-native AI infrastructure company, has launched MCP AdaptiveOps, a solution designed to provide engineering teams with a secure and adaptable way to build and operate Model Context Protocol (MCP) servers. This framework addresses the evolving MCP ecosystem by offering production-ready servers with service levels, while maintaining flexibility for emerging standards.
MCP AdaptiveOps offers a balanced approach to early adoption, drawing from Mirantis' experience with Kubernetes and OpenStack. "MCP is rapidly becoming the standard for connecting enterprise services into agentic infrastructure, but the ecosystem is still shifting," said Randy Bias, vice president of open source strategy and technology at Mirantis. The solution ensures teams can innovate without being locked into outdated assumptions, accelerating delivery while mitigating risks.
MCP AdaptiveOps delivers comprehensive support for enterprise-scale MCP deployments:
This addresses Gartner's prediction that over 40% of agentic AI projects could be canceled by 2027 due to costs, unclear value, or risk issues, emphasizing ROI-focused pursuits.
Mirantis serves leading enterprises like Adobe, Ericsson, Inmarsat, MetLife, PayPal, and Societe Generale. The launch positions the company to guide organizations through the maturing MCP landscape, reducing deployment complexities in AI infrastructure.
MCP AdaptiveOps empowers enterprises to adopt agentic AI confidently, providing reliability and adaptability in a rapidly evolving ecosystem. For details, visit the Mirantis MCP AdaptiveOps page or read the blog post, Securing Model Context Protocol for Mass Enterprise Adoption.
Mirantis delivers the fastest path to enterprise AI at scale, with full-stack AI infrastructure technology that removes GPU infrastructure complexity and streamlines operations across the AI lifecycle, from Metal-to-Model. Today, all infrastructure is AI infrastructure, and Mirantis provides the end-to-end automation, enterprise security and governance, and deep expertise in Kubernetes orchestration that organizations need to reduce time to market and efficiently scale cloud native, virtualized, and GPU-powered applications across any environment – on-premises, public cloud, hybrid or edge.
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