From "Vibes" to Production: Eliminating RAG Data Silos with MCP
summary
Moves a prototype RAG setup into production by replacing fragile, stale-vector workflows with a live Model Context Protocol server that calls multiple connectors in real time. Shows a working python + FastAPI demo that hosts a local MCP server, registers a get_ticket_details tool, and invokes grock Llama 3.3 to choose tools and translate raw API errors into user‑friendly text. Covers live reads and writes, human‑in‑the‑loop approval, audit logging, and scaling to hundreds or thousands of tools.
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chapters (12)
- 0:00AI challenges and Vibe coding
- 3:12Data fragmentation and security
- 5:00What is MCP and architecture
- 8:33MCP integration with LLMs and tools
- 13:08MCP vs traditional RAG
- 18:51Developer ecosystem and languages
- 19:55Production security and human-in-loop
- 22:00Live demo setup and client init
- 24:09MCP tools and ticket schema
- 27:17LLM setup and tool integration
- 30:10MCP server real-time query
- 31:55Q&A
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