# engram

> Use this tool when you need to store and retrieve notes and files with temporal context and citation capabilities. It solves problems related to knowledge management and information retrieval by providing a private memory layer for agents to query and persist memories. The engram tool accepts notes and files as inputs and outputs queried memories via the Model Context Protocol.

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

## Description

Local, private memory layer for notes and files with temporal reasoning and citation. Enables agents to query and persist memories via the Model Context Protocol.

## 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:** mcp-remote
- **Runtime environment:** api
- **Category:** file-system
- **Updated:** 2026-09-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ew8peeo661)
- **Repository:** <https://github.com/jnMetaCode/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": "jnmetacode-engram"
    }
  }
}
```

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