Elasticsearch 7.x MCP Server

An MCP server for Elasticsearch 7.x, providing compatibility with Elasticsearch 7.x versions.

Features

• Provides an MCP protocol interface for interacting with Elasticsearch 7.x
• Supports basic Elasticsearch operations (ping, info, etc.)
• Supports complete search functionality, including aggregation queries, highlighting, sorting, and other advanced features
• Easily access Elasticsearch functionality through any MCP client

Requirements

• Python 3.10+
• Elasticsearch 7.x (7.17.x recommended)

Installation

Installing via Smithery

To install Elasticsearch 7.x MCP Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @imlewc/elasticsearch7-mcp-server --client claude

Manual Installation

pip install -e .

Environment Variables

The server requires the following environment variables:

• ELASTIC_HOST: Elasticsearch host address (e.g., http://localhost:9200)
• ELASTIC_USERNAME: Elasticsearch username
• ELASTIC_PASSWORD: Elasticsearch password
• MCP_PORT: (Optional) MCP server listening port, default 9999

Using Docker Compose

1. Create a .env file and set ELASTIC_PASSWORD:

ELASTIC_PASSWORD=your_secure_password

2. Start the services:

docker-compose up -d

This will start a three-node Elasticsearch 7.17.10 cluster, Kibana, and the MCP server.

Using an MCP Client

You can use any MCP client to connect to the MCP server:

from mcp import MCPClient

client = MCPClient("localhost:9999")
response = client.call("es-ping")
print(response)  # {"success": true}

API Documentation

Currently supported MCP methods:

• es-ping: Check Elasticsearch connection
• es-info: Get Elasticsearch cluster information
• es-search: Search documents in Elasticsearch index

Search API Examples

Basic Search

# Basic search
search_response = client.call("es-search", {
    "index": "my_index",
    "query": {
        "match": {
            "title": "search keywords"
        }
    },
    "size": 10,
    "from": 0
})

Aggregation Query

# Aggregation query
agg_response = client.call("es-search", {
    "index": "my_index",
    "size": 0,  # Only need aggregation results, no documents
    "aggs": {
        "categories": {
            "terms": {
                "field": "category.keyword",
                "size": 10
            }