# odigo-elastic-s2l-mcp

> Use this tool when you need to bridge the gap between Large Language Models (LLMs) and Elasticsearch, enabling autonomous querying without hardcoded domain logic. It solves problems of technical field name translation, allowing for more intuitive and business-friendly searches. The tool takes in LLM queries and outputs relevant Elasticsearch results, making it ideal for use cases where technical expertise is limited.

Canonical page: https://skillsregistry.net/skills/rbeg1-odigo-elastic-s2l-mcp  
JSON: https://api.skillsregistry.net/v1/skills/rbeg1-odigo-elastic-s2l-mcp

## Description

Connects LLMs to Elasticsearch with a Semantic-to-Lexical layer that translates technical field names into business knowledge, enabling autonomous querying without hardcoded domain logic.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/mjbjlfnh7v)
- **Repository:** <https://github.com/rbeg1/odigo-elastic-s2l-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": "rbeg1-odigo-elastic-s2l-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/rbeg1-odigo-elastic-s2l-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/rbeg1-odigo-elastic-s2l-mcp/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