The MCP protocol, and how it changes the way AI agents access data

LLMs are powerful but limited—they operate as isolated systems and struggle with complex, multi-step tasks or integration with enterprise data sources.

The Model Context Protocol (MCP) addresses these gaps by providing a standard way to orchestrate multiple AI agents, models, and tools. MCP enables agents to collaborate, share context, and access structured data, which is essential for advanced analytics.

DataSpaces offers a secure, governed environment for sharing and analyzing data across organizations.

Integrating MCP with DataSpaces allows AI agents to access enterprise data securely, automate analytics workflows, and deliver more actionable insights. This combination extends the capabilities of LLMs, making advanced data analytics more flexible, interoperable, and enterprise-ready.

Speaker: Matthias Buchhorn-Roth
Matthias is a data and AI solutions architect with experience in Cloud Computing, Dataspaces. He is worked closely with Microsoft technologies, including Azure-based data solutions. Currently his focus is on building scalable, user-centric and Agentic AI systems along user journeys and new technologies like Model Context Protocol.