# Easysearch

> Use this tool when you need to manage and interact with Elasticsearch and OpenSearch clusters efficiently. It provides a unified interface for cluster management, index operations, document handling, and search queries, solving problems related to data indexing, searching, and administration. Ideal for use cases requiring comprehensive search functionality, data management, and cluster monitoring, it accepts various inputs and outputs through its async HTTP interface.

Canonical page: https://skillsregistry.net/skills/cloudsmithy-easysearch  
JSON: https://api.skillsregistry.net/v1/skills/cloudsmithy-easysearch

## Description

Provides comprehensive integration with Elasticsearch and OpenSearch clusters through a unified interface compatible with INFINI Easysearch. Built with httpx for async HTTP operations, this server offers tools for cluster management, index operations, document handling, search queries, snapshot management, and administrative tasks like ILM policies and node monitoring.

## Trust

- **Trust score (0–1):** 0.97
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

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

## Source

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

## 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": "cloudsmithy-easysearch"
    }
  }
}
```

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