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MCP, Vector DBs: Memory and Action
Explore how vector databases provide semantic memory for LLMs while Model Context Protocol enables real‑time API access, with examples, trade‑offs, and integration patterns.
In this talk, I’ll explore the difference between Model Context Protocol (MCP) and Vector Databases, and explain how they work together to power the next generation of intelligent AI systems.
We’ll look at how Vector Databases enable semantic search and long-term memory for large language models, while MCP allows models to securely access live, dynamic data and perform real-time actions through APIs or databases.
Through practical examples, like using AI to search and report on enterprise SharePoint data. I’ll show when to use each approach, their strengths and trade-offs, and why combining them creates a more powerful, context-aware AI architecture.
By the end of this session, you’ll understand how memory (Vector DB) and action (MCP) complement each other to move beyond static RAG pipelines toward adaptive, real-time AI systems.