Please Wait...
Please Wait...
A critical first step in operationalizing agentic AI
Gartner predicts massive adoption as platform engineering teams prioritize MCP implementation. The protocol works with Agent-to-Agent coordination to form the backbone of scalable, multi-agent environments that require regionalized infrastructure, container-native compute, and runtime-ready protocol support.
Get started with
world’s largest privately-held cloud
infrastructure company
Model Context Protocol: The Integration Backbone for Scalable Agentic AI
The center of modern agent infrastructure, MCP offers a runtime layer that abstracts internal tools and workflows into secure, modular capabilities.
Traditional APIs built for stateless services can't scale for autonomous AI agents that need dynamic discovery. Most companies view AI agents as the new enterprise apps, yet rigid integrations break under autonomous workflow demands.
MCP replaces brittle integrations with secure, modular capabilities that agents can invoke at runtime. Built on JSON-RPC 2.0, the protocol exposes tools, resources, and prompts through container-native environments with policy enforcement and logging as defaults.
