What are the dependencies for Elasticsearch MCP Server?
Python 3.7+, the Elasticsearch Python client, and the MCP SDK are required. Elasticsearch cluster credentials (Cloud ID and API Key) must be provided.
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基本信息
Elasticsearch MCP Server in Python
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"es_mcp_server": {
"command": "python",
"args": [
"configure_mcp_server.py",
"your_cloud_id",
"your_api_key"
]
}
}
}Lists all indices in the Elasticsearch cluster
Gets the mappings for a specific index
Performs an Elasticsearch search with a provided query DSL
Performs a search with a simple query string
Gets statistics for a specific index
Elasticsearch MCP Server is an MCP (Model Context Protocol) server that provides tools and resources to interact with Elasticsearch clusters. It is designed for developers and AI agents using MCP-compatible clients like Claude.
Install dependencies, set environment variables ES_CLOUD_ID and ES_API_KEY, then run python es_mcp_server.py. Optionally use configure_mcp_server.py to add the server to Claude's MCP settings.
Python 3.7+, the Elasticsearch Python client, and the MCP SDK are required. Elasticsearch cluster credentials (Cloud ID and API Key) must be provided.
Run `configure_mcp_server.py your_cloud_id your_api_key` to add the server to Claude’s MCP settings file. After that, restart VS Code to apply the changes.
Tools: `list_indices`, `get_mappings`, `search`, `search_with_query_string`, `get_index_stats`. Resources: `elasticsearch://indices`, `elasticsearch://index/{index_name}`, `elasticsearch://mapping/{index_name}`.
Use the provided `test_es_mcp.sh` script or start the server manually and test resources via Claude’s `access_mcp_resource` tool. A Python test script `test_es_resources.py` is also included.
All resources catch connection issues, missing indices, and other exceptions, returning clear error messages instead of crashing.

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