# engram

> Use this tool when you need to enhance memory recall and entity relationships in complex systems, as it solves problems related to information retrieval and codebase scanning. Engram provides a hybrid retrieval system, multiple memory layers, and an entity graph, accepting various inputs and generating outputs to facilitate efficient recall and scanning. It is ideal for use cases involving large codebases, complex data relationships, and memory-intensive applications.

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

## Description

A cognitive memory system for MCP that provides hybrid retrieval, memory layers, entity graph, and 83 tools for recall, remember, codebase scanning, and more.

## Trust

- **Trust score (0–1):** 0.49
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/bcewcvb5v8)
- **Repository:** <https://github.com/raya-ac/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": "raya-ac-engram"
    }
  }
}
```

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