Azure AI MCP Elasticsearch Agent

Example Use Cases

• 1

  Perform natural language search queries on Elasticsearch data.

• 2

  That require secure remote access to MCP servers via Azure DevTunnels.

• 3

  Integrate Azure AI Foundry capabilities with Elasticsearch backend.

Description

This project provides a Python-based Azure AI Foundry agent that communicates with an MCP (Model Context Protocol) server to interact with Elasticsearch data. It supports secure connections via Azure DevTunnels, smart tool filtering for safety, and asynchronous operations for performance. The agent enables natural language conversations to search, analyze, and retrieve Elasticsearch information, making it suitable for building intelligent search assistants.