Corby Page

The rise of agentic AI has fundamentally changed how we think about application integration. AI agents are no longer passive responders. They’re active participants that discover, invoke, and orchestrate tools to accomplish complex tasks. At the heart of this shift is the Model Context Protocol (MCP), an open standard that enables AI agents to interact with external tools and data sources through a natural language interface.

Getting a new AI agent to production introduces significant complexity to the software development and delivery cycle. Enterprise developers need secure, compliant access to many services and resources including Large Language Models (LLMs), Vector Databases, Agent Registry, Conversation Memory, a Message Bus, and more. Access to these services that also enables integrated security and governance capabilities can be achieved more easily with a platform like Tanzu Platform with Tanzu AI Solutions.

REST APIs are extremely attractive for their design elegance. You get something that Google’s Adam Bosworth describes as “simple, relaxed, sloppily extensible,” but you do not get something built for consistent performance. Existing REST frameworks do a great job of converting your domain model to a JSON or XML response. However, they operate under the assumption that each resource has a single document view.