MCP Server Elasticsearch
The Elasticsearch MCP Server project enables natural - language interactive queries of Elasticsearch data through the Model Context Protocol (MCP).
rating : 3 points
downloads : 707
What is the Elasticsearch MCP Server?
The Elasticsearch MCP Server is a tool that connects to Elasticsearch data sources, allowing you to interact with Elasticsearch indexes through natural language conversations.How to use the Elasticsearch MCP Server?
You can start using it in just a few steps: install the configuration file, start the server, and start asking questions.Use Cases
Suitable for enterprise and individual users who need to quickly query and analyze Elasticsearch indexes.Main Features
List IndexesList all indexes in the current Elasticsearch instance.
Get MappingsGet the field mapping information of a specific index.
Perform SearchPerform a search operation based on the provided query DSL.
Get Shard InformationGet the shard information of all or specific indexes.
Advantages and Limitations
Advantages
Interact with Elasticsearch data through natural language.
Support multiple query methods to meet diverse needs.
Simplify complex query processes and improve work efficiency.
Limitations
Appropriate permission settings are required to ensure data security.
It has a certain dependence on the Elasticsearch version.
How to Use
Installation and Configuration
Download and configure the NPM package of the Elasticsearch MCP Server.
Start the Server
Add configuration to the MCP client and start the server.
Start Asking Questions
Send natural language query requests directly to the MCP client.
Usage Examples
List All IndexesQuery all indexes in the Elasticsearch instance.
Get the Field Mapping of the Product IndexView the product field mapping of a specific index.
Frequently Asked Questions
How to ensure data security?
Does it support custom SSL certificates?
How to debug the server?
Related Resources
Official Documentation
Detailed official documentation and tutorials.
GitHub Repository
Open - source code and contribution guidelines.
Featured MCP Services

Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
1.7K
5 points

Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
823
4.3 points

Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
79
4.3 points

Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
130
4.5 points

Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
554
5 points

Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
6.6K
4.5 points

Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
5.2K
4.7 points

Minimax MCP Server
The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.
Python
745
4.8 points