E

Es MCP Server

This project implements an MCP server for Elasticsearch, providing tools and resources for interacting with the Elasticsearch cluster, including functions such as index listing, mapping retrieval, and search, and supporting access to Elasticsearch data through the MCP protocol.
2.5 points
21

What is the Elasticsearch MCP Server?

This is an MCP server specifically designed for Elasticsearch, allowing users to interact with the Elasticsearch cluster through standard protocols. It simplifies common operations such as index management, data search, and statistical analysis.

How to use the Elasticsearch MCP Server?

You can set connection parameters through configuration scripts and then use the provided tools or resource URIs to query Elasticsearch data. It supports command-line testing and integration into various usage scenarios such as Claude.

Applicable scenarios

Suitable for scenarios where Elasticsearch data needs to be integrated into AI workflows, such as data analysis, content retrieval, and log analysis. It is particularly suitable for use with AI assistants like Claude.

Main features

Index listGet a list of all indices in the Elasticsearch cluster and their basic information
Mapping queryView the data structure and field type definitions of a specific index
Advanced searchPerform complex searches using the Elasticsearch query DSL
Simple searchPerform a quick search using simplified query string syntax
Index statisticsGet statistical information such as the number of documents and storage size of an index

Advantages and limitations

Advantages
Simplify access to the Elasticsearch cluster without directly dealing with complex APIs
Standardized interface, easy to integrate into various AI workflows
Provide multiple query methods to meet the needs of users with different technical levels
Detailed error handling to help quickly locate problems
Limitations
Requires pre - configuration of Elasticsearch connection information
Does not support all native Elasticsearch functions
Performance may be slightly lower than direct API calls

How to use

Install dependencies
Ensure that Python 3.7+ and necessary dependency packages are installed
Configure connection
Set the Cloud ID and API Key of the Elasticsearch cluster
Start the server
Run the main program to start the MCP server
Test the connection
Use the test script to verify the server functionality

Usage examples

Query the product indexGet the structural information of the product index on the e - commerce platform
Search log dataSearch for specific error information in the log index
Cluster health checkCheck the health status of all indices in the cluster

Frequently Asked Questions

How to solve the connection failure problem?
What if the query returns an empty result?
How to improve query performance?
Which Elasticsearch versions are supported?

Related resources

Elasticsearch official documentation
Complete official documentation for Elasticsearch
MCP protocol specification
Official specification document for the Model Context Protocol
GitHub repository
Project source code and latest updates
Python Elasticsearch client
Official Python client documentation used in this project
Installation
Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.
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