Elasticsearch MCP Server for AI Agents

Overview

The Elasticsearch MCP Server connects your data to AI agents via the Model Context Protocol (MCP), enabling natural language interaction with your indices. It exposes Elasticsearch indices as secure, searchable resources, allowing LLMs to perform powerful retrieval and analysis.

With Elasticsearch's open-source vector database, agent builders already have the tools for fast, scalable retrieval. The MCP Server extends those capabilities, making it easier than ever to build and deploy agentic applications at scale.

Support for Streamable HTTP Transport: Enables HTTP POST and optional SSE-based streaming -- ideal for web integrations, stateful sessions, and concurrent clients.

For more information, please visit Elastic Cloud (Elasticsearch Service) at https://aws.amazon.com/marketplace/pp/prodview-voru33wi6xs7k  or elastic.co. The MCP server is provided as a Docker container that uses a minimal, hardened container base image that can be used for easy deployment and scaling within your AWS environment.

Highlights

• Built on Elasticsearch's open source, scalable vector database: Fast, high-quality retrieval across structured and unstructured data.

• Easy integration with agents, IDEs, and developer tools. Connect tools like Claude Desktop, VSCode, Cursor, or your own agent -- no re-architecture required.

• Access key Elasticsearch capabilities. list_indices to help agents discover available data, get_mappings to understand field structure, get_shards to get shard information for all or specific indices, and search to run powerful queries using Elasticsearch DSL -- the core tools the server provides to help Agents take meaningful actions.