# Engram

> Engram — lofder-engram. Use this tool when you need to efficiently manage and recall memories for multiple AI agents, enabling seamless interaction and knowledge sharing. Engram solves problems of scalable memory architecture, agent collaboration, and knowledge retrieval, accepting inputs from various sources and outputting relevant information for informed decision-making. Ideal for multi-agent systems, Engram streamlines memory management, enhancing overall AI performance and coordination.

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

## Description

Scope-aware memory architecture for multi-agent AI assistants. Powered by Mem0 + Qdrant + MCP.

## Trust

- **Trust score (0–1):** 0.63
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/lofder/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": "lofder-engram"
    }
  }
}
```

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