# engram

> Use this tool when you need to enhance AI assistants with personal semantic memory, enabling them to store and recall information by meaning. Engram solves the problem of knowledge retention and retrieval for AI tools, providing a self-hosted server for hybrid vector and keyword search. It takes in memories and outputs relevant information, ideal for use cases where AI assistants require contextual understanding and recall of previous interactions.

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

## Description

A self-hosted MCP server that provides a personal semantic memory layer for AI tools. It enables storing, searching, and managing memories using hybrid vector and keyword search, allowing AI assistants to recall information by meaning.

## Trust

- **Trust score (0–1):** 0.66
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/f7zg4ilt77)
- **Repository:** <https://github.com/jblacketter/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": "jblacketter-engram"
    }
  }
}
```

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