# engram

> engram — the-long-ride-engram. Use this tool when you need to manage and synchronize AI agent memory across multiple projects, devices, and teams. Engram solves the problem of fragmented knowledge and data silos by providing a unified, file-system-based memory management system. It integrates with git, allowing for seamless version control and collaboration, and is ideal for use cases where knowledge sharing and consistency are crucial.

Canonical page: https://skillsregistry.net/skills/the-long-ride-engram  
JSON: https://api.skillsregistry.net/v1/skills/the-long-ride-engram

## Description

Engram - file-system-based memory management system for AI agents that grows with you & your teams, across agents, projects, and devices.

## Trust

- **Trust score (0–1):** 0.77
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** GPL-3.0
- **Updated:** 2026-09-28

## Source

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

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