# engram

> Use this tool when you need to extract and store atomic facts from text, link them to entities and relationships, and synthesize higher-order observations. It solves problems related to information retrieval, knowledge graph construction, and insight generation, taking in text data and outputting linked facts and synthesized observations. Ideal for use cases requiring automated knowledge extraction and pattern discovery from unstructured text.

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

## Description

An MCP server that stores atomic facts extracted from text, links them to entities and relationships, and synthesizes higher-order observations (patterns, preferences, insights) via a reflect loop.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/al5mzt0294)
- **Repository:** <https://github.com/ReallyArtificial/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": "reallyartificial-engram"
    }
  }
}
```

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