# engram

> engram — ricoaiproject-cmd-engram. Use this tool when you need to leverage a human-like memory base for AI agents, enabling long-term memory sharing and recall through Claude Code, Codex, or Antigravity. It solves problems related to knowledge retention and retrieval, allowing AI agents to learn and improve over time. With git capabilities, it integrates seamlessly into development workflows, accepting code inputs and generating shared memory outputs.

Canonical page: https://skillsregistry.net/skills/ricoaiproject-cmd-engram  
JSON: https://api.skillsregistry.net/v1/skills/ricoaiproject-cmd-engram

## Description

AIエージェント用 人間型記憶基盤（MCPサーバー）— 完全日本語版。使うほど思い出しやすくなる長期記憶を Claude Code / Codex / Antigravity で共有

## Trust

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

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/ricoaiproject-cmd/engram)

## 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": "ricoaiproject-cmd-engram"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ricoaiproject-cmd-engram` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ricoaiproject-cmd-engram/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