Nutanix brings agentic AI automation to hybrid multi-cloud environments

In August 2026, Nutanix recently launched an open-source Model Context Protocol (MCP) server for Nutanix Cloud Platform, which helps in enabling enterprises to use AI assistants and agents to automate cloud operations through natural-language commands while retaining existing security and governance controls.

The MCP server connects AI tools such as GitHub Co-pilot, Claude Code, and Cursor with Nutanix Cloud Platform through the Prism v4 API, translating plain-English requests into infrastructure actions. The approach is designed to help IT teams automate routine operations across hybrid mult-icloud environments without sacrificing visibility or operator oversight.

The MCP server also operates as a secure gateway between AI tools and the Nutanix platform. Because execution is handled through the Prism v4 API Gateway, connected AI tools can inherit Nutanix’s existing access controls and governance mechanisms. Teams can now use AI to analyze system health, surface diagnostics, and stage automation workflows while simultaneously retaining human-in-the-loop controls.

This launch also represents Nutanix’s move to extend its existing cloud automation capabilities into agentic AI, allowing enterprises to build custom AI-driven workflows while keeping infrastructure execution subject to established security, access, and governance policies.

Impact on the AI Market

Key capabilities of this launch include fine-grained role-based access control, throttling and API metering, comprehensive auditing, and asynchronous task management. These controls allow organizations to restrict AI agents to authorized APIs, monitor usage, prevent excessive automated traffic, and track which agent initiated a particular command.

For developers, the MCP server can also provide AI coding assistants with system blueprints to generate infrastructure scripts in languages and formats, including Python, Go, Java, JavaScript, PowerShell, curl, REST, and JSON.

Impact on the Cloud Infrastructure Services Market

The global cloud infrastructure services market size accounted for USD 166.51 billion in 2025 and is predicted to increase from USD 194.82 billion in 2026 to approximately USD 766.57 billion by 2035, expanding at a CAGR of 16.50 % from 2026 to 2035. 

According to Precedence Research, the market is driven by growing adoption of artificial intelligence, increasing demand for scalable computing, and rising enterprise digital transformation. Cloud providers invest heavily in security measures and compliance certifications. This enhances data protection, access control, and regulatory compliance, addressing concerns related to the security of sensitive information and ensuring adherence to industry-specific regulations.

The expanding landscape of edge computing is also helping in creating significant opportunities for the cloud infrastructure services market. As edge computing gains prominence, there is a growing need for decentralized infrastructure that brings computational power closer to data sources. Cloud infrastructure services can capitalize on this trend by developing solutions tailored to edge environments. Offering scalable and flexible resources for processing data at the edge allows businesses to optimize performance, reduce latency, and enhance overall efficiency. Cloud providers that strategically position themselves to meet the demands of edge computing scenarios can unlock new revenue streams and cater to industries requiring real-time data processing capabilities.

Impact on the Agentic AI in Enterprise Operations Market

The global agentic AI in enterprise operations market is driven by the rise of AI-powered agents that adapt, learn, and act within enterprise ecosystems. The market is experiencing significant growth, led by rapid digital transformation, increasing demand for autonomous decision-making for business activities, and increasing integration of AI with enterprise software.

According to Precedence Research, connectivity and compatibility with ERPs, CRMs, and Supply Chain Management systems are important accelerants for the adoption of AI tools in enterprises, especially when the tool works natively on the enterprise information systems that exist, so the enterprise can realize value quickly. Organizations are under pressure to reduce costs, reduce mistakes in processes, and return on investments. Agentic AI automates repetitive, resource-consuming tasks with greater accuracy and smarts that improve efficiencies and free up employees to do the strategic portions of their jobs.

The agentic AI in the enterprise operations market is driven by the shift to hyper-personalization at scale. Unlike legacy automation approaches, agentic AI can learn user preferences dynamically, autonomously reconfigure workflows, and respond contextually across various enterprise functions. The growth of agentic AI is, to a certain extent, tied to the growing demand for organizations to make autonomous decisions. Agentry AI offers organizations the potential for lower manual intervention in tasks, contributory workflows, and acquisition agility in open environments. Initial applications that can be observed are real-time uses of agentic AI, such as AI-driven intelligent customer service agents, financial risk assessments, autonomous supply chain and logistics platforms, and workflows. 

Expert Opinion

“By creating a secure gateway between AI tools and our platform, we are giving customers the confidence to safely use AI to operate and govern their hybrid multi-cloud environments,” said Thomas Cornely, Executive Vice President, Product Management, Nutanix.