# Elasticsearch Knowledge Graph

> Use this tool when you need to efficiently store and retrieve complex entity relationships, or perform advanced searches with fuzzy matching and relevancy ranking. It solves problems related to scalable data storage, entity management, and knowledge retrieval, providing a performant solution for large datasets. The Elasticsearch Knowledge Graph accepts entity and relation data as input and outputs relevant search results, prioritizing recently accessed and important information.

Canonical page: https://skillsregistry.net/skills/j3k0-elastic-memory  
JSON: https://api.skillsregistry.net/v1/skills/j3k0-elastic-memory

## Description

This Elasticsearch-based knowledge graph implementation for MCP replaces the previous JSON file-based approach with a scalable, performant solution. It provides distributed storage for entities and relations, advanced search capabilities with fuzzy matching and relevancy ranking, and complete CRUD operations. The system tracks access patterns to prioritize recently viewed and important entities, simulating memory-like behavior where important, recent, and frequently accessed information rises to the top. Built with TypeScript and the Elasticsearch client, it includes tools for migration, management, and maintenance through a comprehensive admin CLI.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-04-25

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/j3k0-elastic-memory)
- **Repository:** <https://github.com/j3k0/mcp-brain-tools>

## 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": "j3k0-elastic-memory"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/j3k0-elastic-memory` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/j3k0-elastic-memory/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