Listen "Agentic AI, Model Context Protocol and Data Products"
Episode Synopsis
Welcome to another episode of Data Architecture Elevator, hosted by Paolo Platter (https://www.linkedin.com/in/paoloplatter/) and featuring Antonino Ingargiola (https://www.linkedin.com/in/antonino-ingargiola/) and Antonio Murgia (https://www.linkedin.com/in/antonio-murgia/).
The conversation explores how Model Context Protocol (MCP), introduced by Anthropic, enables interoperability between LLM-based agentic applications and external systems through a standardized client-server model. In this setup, agents (LLM clients) discover and invoke tools exposed by MCP-compliant servers. This protocol decouples integration logic, allowing systems to interoperate without custom code. The discussion then applies MCP to data products in a data mesh architecture, where output ports (data access), observability ports (data quality and freshness), and control ports (operations) can be exposed as tools via MCP. This allows agents to autonomously query data, evaluate its quality, and even trigger operational commands like restarts or compliance actions.
Enjoy it :)
The conversation explores how Model Context Protocol (MCP), introduced by Anthropic, enables interoperability between LLM-based agentic applications and external systems through a standardized client-server model. In this setup, agents (LLM clients) discover and invoke tools exposed by MCP-compliant servers. This protocol decouples integration logic, allowing systems to interoperate without custom code. The discussion then applies MCP to data products in a data mesh architecture, where output ports (data access), observability ports (data quality and freshness), and control ports (operations) can be exposed as tools via MCP. This allows agents to autonomously query data, evaluate its quality, and even trigger operational commands like restarts or compliance actions.
Enjoy it :)
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Espresso - Data Science and Data Engineering
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Espresso - MLOps
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Espresso - FinOps
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