What is the Elasticsearch MCP Server?
It is an MCP server that exposes Elasticsearch operations (index, document, and cluster management) as callable tools for AI assistants like Claude.
@MCP-Mirror
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A Model Context Protocol (MCP) server implementation that provides Elasticsearch interaction. It enables searching documents, analyzing indices, and managing a cluster through a set of tools, designed for use with MCP clients like Claude Desktop.
Configure the server in your MCP client (e.g., Claude Desktop) by setting environment variables ELASTIC_HOST, ELASTIC_USERNAME, and ELASTIC_PASSWORD to point to your Elasticsearch cluster. Use the provided tools via natural language commands, such as "List all indices in the cluster" or "Show me the cluster health status."
list_indices: List all indices in the Elasticsearch cluster.get_mapping: Retrieve mapping configuration for a specific index.get_settings: Get settings configuration for a specific index.search_documents: Search documents using Elasticsearch Query DSL.get_cluster_health: Get health status of the cluster.get_cluster_stats: Get statistical information about the cluster.It is an MCP server that exposes Elasticsearch operations (index, document, and cluster management) as callable tools for AI assistants like Claude.
Set the `ELASTIC_HOST`, `ELASTIC_USERNAME`, and `ELASTIC_PASSWORD` environment variables in your MCP client configuration to match your cluster’s credentials.
The server provides six tools: `list_indices`, `get_mapping`, `get_settings`, `search_documents`, `get_cluster_health`, and `get_cluster_stats`.
You need an Elasticsearch cluster (local or remote) and the MCP server running via `uv` (Python). A sample Docker Compose file is provided to start a 3-node cluster with Kibana.
Yes, basic authentication is supported via the `ELASTIC_USERNAME` and `ELASTIC_PASSWORD` environment variables. The default credentials in the provided Docker Compose are `elastic` / `test123`.

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