# io.github.omega-memory/core

> Use this tool when you need to persist data locally for AI coding agents, solving problems of data loss and synchronization across sessions. It provides a local-first approach to memory management, allowing agents to store and retrieve information efficiently. Ideal for use cases requiring durable storage, such as long-term evaluations and continuous learning scenarios.

Canonical page: https://skillsregistry.net/skills/io-github-omega-memory-core  
JSON: https://api.skillsregistry.net/v1/skills/io-github-omega-memory-core

## Description

Persistent memory for AI coding agents. #1 on LongMemEval. 26 MCP tools. Local-first.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 0.8.2
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-04-19

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.github.omega-memory%2Fcore)
- **Repository:** <https://github.com/omega-memory/core>

## 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": "io-github-omega-memory-core"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/io-github-omega-memory-core` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/io-github-omega-memory-core/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