Overview

The Elasticsearch MCP Server provides a robust bridge for AI models to interact with Elasticsearch and OpenSearch. It enables searching documents, analyzing indices, and managing clusters through a standardized set of tools, making it a crucial component for AI-driven data exploration and management.

Created by:

Developed by cr7258

Key Features

🔍

Document Search & Management

Search, index, get, and delete documents within Elasticsearch indices

📊

Index & Cluster Operations

Manage indices (create, delete, get mappings) and monitor cluster health

🔗

Alias Management

Create, update, and delete index aliases for flexible data routing

🛡️

Security & Control

Option to disable high-risk write operations for enhanced safety

Available Tools

Quick Reference

Tool	Purpose	Category
`general_api_request`	Perform general HTTP API requests	General
`list_indices`	List all available indices	Index
`get_index`	Get information about indices	Index
`create_index`	Create a new index	Index
`delete_index`	Delete an index	Index
`create_data_stream`	Create a new data stream	Data Stream
`get_data_stream`	Get information about data streams	Data Stream
`delete_data_stream`	Delete data streams	Data Stream
`search_documents`	Search for documents	Document
`index_document`	Create or update a document	Document
`get_document`	Get a document by ID	Document
`delete_document`	Delete a document by ID	Document
`delete_by_query`	Delete documents by query	Document
`get_cluster_health`	Get cluster health information	Cluster
`get_cluster_stats`	Get cluster statistics	Cluster
`list_aliases`	List all aliases	Alias
`get_alias`	Get alias information	Alias
`put_alias`	Create or update an alias	Alias
`delete_alias`	Delete an alias	Alias

Detailed Usage

search_documents▶

Search for documents within specified indices using a query DSL.

use_mcp_tool({
  server_name: "elasticsearch",
  tool_name: "search_documents",
  arguments: {
    index: "my_index",
    query: {
      match: {
        message: "hello world"
      }
    }
  }
});

Returns matching documents and their metadata.

index_document▶

Creates or updates a document in the specified index.

use_mcp_tool({
  server_name: "elasticsearch",
  tool_name: "index_document",
  arguments: {
    index: "my_index",
    id: "1",
    document: {
      user: "John Doe",
      message: "Hello from MCP"
    }
  }
});

If ID is provided, updates existing document; otherwise, creates a new one.

get_cluster_health▶

Returns basic information about the health of the Elasticsearch cluster.

use_mcp_tool({
  server_name: "elasticsearch",
  tool_name: "get_cluster_health",
  arguments: {}
});

Provides status (green, yellow, red), node count, and shard information.

list_indices▶

List all available Elasticsearch indices.

use_mcp_tool({
  server_name: "elasticsearch",
  tool_name: "list_indices",
  arguments: {}
});

Returns a list of all indices in the cluster.

Installation

{
  "mcpServers": {
    "elasticsearch": {
      "command": "uvx",
      "args": [
        "elasticsearch-mcp-server"
      ],
      "env": {
        "ELASTICSEARCH_HOSTS": "https://localhost:9200",
        "ELASTICSEARCH_USERNAME": "elastic",
        "ELASTICSEARCH_PASSWORD": "your_password"
      }
    }
  }
}

API Key Authentication:

Alternatively, use ELASTICSEARCH_API_KEY for authentication:

{
  "mcpServers": {
    "elasticsearch": {
      "command": "uvx",
      "args": [
        "elasticsearch-mcp-server"
      ],
      "env": {
        "ELASTICSEARCH_HOSTS": "https://localhost:9200",
        "ELASTICSEARCH_API_KEY": "YOUR_ELASTICSEARCH_API_KEY"
      }
    }
  }
}

Common Use Cases

1. Document Search

Search for specific documents based on keywords or complex queries:

use_mcp_tool({
  server_name: "elasticsearch",
  tool_name: "search_documents",
  arguments: {
    index: "products",
    query: {
      bool: {
        must: { match: { name: "laptop" } },
        filter: { range: { price: { gte: 500, lte: 1500 } } }
      }
    }
  }
});

2. Indexing New Data

Add new data to an Elasticsearch index:

use_mcp_tool({
  server_name: "elasticsearch",
  tool_name: "index_document",
  arguments: {
    index: "logs",
    document: {
      timestamp: new Date().toISOString(),
      level: "info",
      message: "User logged in successfully"
    }
  }
});

3. Monitoring Cluster Health

Periodically check the health of the Elasticsearch cluster:

use_mcp_tool({
  server_name: "elasticsearch",
  tool_name: "get_cluster_health",
  arguments: {}
});

4. Managing Index Aliases

Create an alias for an index to simplify queries or manage reindexing:

use_mcp_tool({
  server_name: "elasticsearch",
  tool_name: "put_alias",
  arguments: {
    index: "products_v1",
    name: "current_products"
  }
});

Connection String Format

The Elasticsearch MCP server primarily uses environment variables for connection details, but the underlying Elasticsearch client supports various connection methods.

Host: ELASTICSEARCH_HOSTS (e.g., https://localhost:9200)
Authentication:
- ELASTICSEARCH_USERNAME and ELASTICSEARCH_PASSWORD for basic auth.
- ELASTICSEARCH_API_KEY for API key authentication.
SSL Verification: ELASTICSEARCH_VERIFY_CERTS (default: false)

Sources

Google Drive MCP Server

Google Drive MCP servers enable AI models to interact with Google Drive, providing capabilities for file search, content retrieval, and seamless integration with cloud storage.

Docker MCP Server

Manage Docker containers, images, networks, and volumes through AI assistants using natural language with the Docker MCP Server.

Google Maps MCP Server

Google Maps MCP server provides AI assistants with location-based services including places search, directions, geocoding, elevation data, and detailed place information.

Elasticsearch MCP Server