MCP Dev Summit Seoul 2026

Most standard RAG pipelines treat data retrieval as a blunt instrument: run a basic search and stuff the context window. At Elastic, we used the Model Context Protocol to build a much smarter, agent-driven retrieval system. In this talk, I’ll show you how we built our MCP server to focus on dynamic context engineering rather than hardcoded pipelines.

I’ll break down our strategy of giving agents atomic tools to inspect the data environment first. By exposing capabilities like list_indices and get_mappings, the agent gathers the exact schema context it needs before writing and executing complex ES|QL or Query DSL.

If you are building an MCP server for your own databases or APIs, I’ll share how this "discover first, search second" approach practically eliminates query hallucinations and creates a highly reliable retrieval loop. You'll walk away with a proven strategy for engineering better context and building smarter data retrieval into your own MCP systems.