Data Management Glossary
Model Context Protocol (MCP)
What is the Model Context Protocol?
The Model Context Protocol (MCP) is an emerging open standard that enables AI models and agents to securely connect with external tools, data sources, and systems in a consistent way. Instead of building one-off integrations, MCP provides a framework for interoperability, allowing agentic AI systems to dynamically pull in context, take actions, and access enterprise resources.
Why MCP important for Agentic AI?
Agentic AI refers to AI systems that can plan, reason, and act autonomously to achieve goals. For these agents to be useful in enterprise environments, they must safely access real-time business data, applications, and workflows. MCP makes this possible by providing a standardized way to extend AI capabilities, enforce security controls, and ensure reliable connections across different ecosystems.
What is the role of Unstructured Data Management & Komprise?
Since up to 80% of enterprise data is unstructured (files, images, genomics data, sensor logs, etc.), agentic AI needs a way to find, classify, and deliver the right unstructured data to its reasoning process. This is where Komprise plays a key role. By analyzing, tiering, and mobilizing petabyte-scale unstructured data without vendor lock-in, Komprise ensures MCP-connected AI agents can access the most relevant, accurate, and policy-compliant data for training, inference, and decision-making, while controlling costs and reducing risks such as exposing sensitive information.
