# Elasticsearch

> Use this tool when you need to analyze log data using natural language queries, identify performance bottlenecks, and optimize system performance. It connects to Elasticsearch clusters, providing intelligent log analysis and actionable recommendations through a user-friendly interface that takes natural language inputs and outputs insightful logs and performance metrics. Ideal for DevOps teams and SRE engineers, it simplifies complex log analysis tasks and accelerates issue diagnosis.

Canonical page: https://skillsregistry.net/skills/y0zg-elasticsearch  
JSON: https://api.skillsregistry.net/v1/skills/y0zg-elasticsearch

## Description

This Elasticsearch MCP server enables AI-powered log analysis by connecting Claude Desktop directly to Elasticsearch clusters, allowing users to query logs using natural language instead of complex Elasticsearch syntax. Built with Python and the FastMCP framework, it provides five specialized tools for searching logs, analyzing error patterns with root cause analysis, detecting performance bottlenecks, monitoring cluster health, and optimizing index performance. The implementation features intelligent time range parsing, automatic error signature extraction, performance trend analysis, and generates actionable recommendations for system optimization, making it ideal for DevOps teams and SRE engineers who need to quickly diagnose issues and gain insights from their log data without writing complex queries.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** devops-ci
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/y0zg-elasticsearch)
- **Repository:** <https://github.com/y0zg/mcp-elasticsearch>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "y0zg-elasticsearch"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/y0zg-elasticsearch` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/y0zg-elasticsearch/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt