MCP Servers for OpenShift AI

AI models are most powerful when they can securely interact with your enterprise data and developer tools. Model Context Protocol (MCP) provides the open standard to make these connections seamless, especially when running on robust enterprise AI platforms. In this course, you will explore the foundational concepts of MCP and learn how to configure, run, and manage MCP servers within an OpenShift AI environment. You will gain the skills to bridge the gap between large language models and external systems, enabling smarter, context-aware AI applications. What you'll learn: - Understand the core architecture and specifications of the Model Context Protocol (MCP). - Configure MCP servers to securely connect AI models with databases, APIs, and enterprise systems. - Deploy and manage MCP workloads within the OpenShift AI ecosystem. - Apply security best practices to control data access and tool usage for AI agents. - Troubleshoot communication and integration issues between AI models and external resources. You will start by learning the essential terminology and architectural basics of MCP before moving on to step-by-step written configuration guides and deployment strategies tailored for OpenShift AI. This course is designed for developers, platform engineers, and AI enthusiasts who want to build connected AI applications, with no prior MCP experience required. Start reading today to unlock the full potential of context-aware enterprise AI.