# Elasticsearch

> Use this tool when you need to perform advanced searches, analyze data, or retrieve index information from Elasticsearch clusters. It solves problems related to data retrieval, semantic searching, and data analysis, particularly in AI-assisted applications. The tool accepts search queries and index information as inputs and returns relevant search results and data insights as outputs.

Canonical page: https://skillsregistry.net/skills/meghanmurphy1-elasticsearch  
JSON: https://api.skillsregistry.net/v1/skills/meghanmurphy1-elasticsearch

## Description

This MCP server implementation provides a bridge to Elasticsearch, enabling AI assistants to interact with Elasticsearch clusters. It offers tools for retrieving index information, performing standard and semantic searches, and analyzing Salesforce data. The server utilizes the FastMCP framework and Elasticsearch Python client, making it suitable for use cases requiring advanced search capabilities and data analysis within AI-assisted applications.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/meghanmurphy1-elasticsearch)
- **Repository:** <https://github.com/meghanmurphy1/mcp>

## 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": "meghanmurphy1-elasticsearch"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/meghanmurphy1-elasticsearch` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/meghanmurphy1-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