# Elasticsearch

> Use this tool when you need to integrate powerful search and analytics capabilities into AI workflows, particularly for managing large datasets. It solves problems like intelligent data retrieval, automated index management, and AI-driven data analysis by providing functionalities such as searching, creating indices, and indexing documents. It takes in queries and dataset inputs, outputting relevant search results and analytics, making it ideal for developers and data scientists working with Elasticsearch environments.

Canonical page: https://skillsregistry.net/skills/da1y-elasticsearch  
JSON: https://api.skillsregistry.net/v1/skills/da1y-elasticsearch

## Description

This Elasticsearch MCP server enables AI models to interact with Elasticsearch clusters, providing tools for managing indices and executing queries. Developed as an open-source project, it integrates with the @elastic/elasticsearch library to offer functionalities like searching, creating indices, listing indices, and indexing documents. The server is built with TypeScript and leverages the @modelcontextprotocol/sdk for MCP implementation. By abstracting Elasticsearch operations, it allows AI systems to easily incorporate powerful search and analytics capabilities into their workflows. This implementation is particularly useful for developers and data scientists working with large datasets, enabling use cases like intelligent data retrieval, automated index management, and AI-driven data analysis in Elasticsearch environments.

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** data-analytics
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/da1y-elasticsearch)
- **Repository:** <https://github.com/da1y/mcp-server-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": "da1y-elasticsearch"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/da1y-elasticsearch` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/da1y-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