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Elasticsearch7-MCP服务器
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Elasticsearch7-MCP服务器

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2025-04-13

Elasticsearch7 MCP服务器

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Elasticsearch 7.x MCP Server

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

Elasticsearch 7.x Server MCP server

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
  1. 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
            }
        },
        "avg_price": {
            "avg": {
                "field": "price"
            }
        }
    }
})

Advanced Search

# Advanced search with highlighting, sorting, and filtering
advanced_response = client.call("es-search", {
    "index": "my_index",
    "query": {
        "bool": {
            "must": [
                {"match": {"content": "search term"}}
            ],
            "filter": [
                {"range": {"price": {"gte": 100, "lte": 200}}}
            ]
        }
    },
    "sort": [
        {"date": {"order": "desc"}},
        "_score"
    ],
    "highlight": {
        "fields": {
            "content": {}
        }
    },
    "_source": ["title", "date", "price"]
})

Development

  1. Clone the repository
  2. Install development dependencies
  3. Run the server: elasticsearch7-mcp-server

License

[License in LICENSE file]

中文文档

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    Reviews

    5 (1)
    Avatar
    user_4wKmZEii
    2025-04-16

    I've been using the elasticsearch7-mcp-server from imlewc and it's been a game-changer for my applications. The seamless integration and robust performance make data management a breeze. The user-friendly interface and comprehensive documentation on GitHub are incredibly helpful. Highly recommend for anyone looking to optimize their elasticsearch usage.