# engram

> engram — jamjet-labs-engram. Use this tool when you need to store and retrieve temporal facts, detect conflicts, and manage hybrid data for AI agents, providing durable memory and reliable information retrieval. It accepts various data inputs and outputs retrieved facts, resolved conflicts, and updated knowledge graphs. Ideal for applications requiring robust and efficient memory management, such as knowledge-intensive AI systems and decision-support models.

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

## Description

Durable memory for AI agents — temporal facts, conflict detection, hybrid retrieval. MCP-native. Apache 2.0.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** Apache-2.0
- **Updated:** 2026-09-28

## Source

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

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