Every MCP-compatible agent in the world needs the same three things from a search backend: discover what data is available, run queries against it, and get structured results back. Claude, Amazon Q, Cursor, Kiro, Strands Agents, and a growing list of open-source frameworks all speak MCP natively now. The protocol side is settled. Your search infrastructure can now speak it back.
Amazon OpenSearch Service now does. Your domain exposes a native MCP endpoint, and agents connect directly. No custom connectors, no middleware, no per-agent integration code. This post walks through what that looks like in practice: what the endpoint exposes, how to secure it, and why the M×N integration problem disappears when your data source speaks the same protocol your agents already understand.
MCP in 60 Seconds
The Model Context Protocol (MCP) is a standard JSON-RPC interface that lets AI agents discover and call tools on external systems. An MCP server advertises what it can do (search an index, check cluster health, run an aggregation), and any MCP-compatible agent can call those tools without custom integration code. One protocol replaces all the bespoke connectors.
The problem MCP solves is combinatorial. If you have M agents connecting to N data sources, custom integrations mean M×N connectors to build and maintain. Three agents talking to five OpenSearch Service domains means fifteen connectors. Each one handles authentication, query formatting, and response parsing in its own way. Add a sixth domain or a fourth agent, and the cycle starts over. MCP collapses that to M+N: each agent speaks one protocol, each data source exposes one server, and any agent can talk to any server without additional code.
