# Memory Graph

> Use this tool when you need to manage long-term user context and preferences across conversations. It solves problems of information fragmentation by organizing facts into connected profiles, enabling richer and more accurate memories. The Memory Graph takes in user details and preferences as input and outputs actionable, updated profiles with extracted locations.

Canonical page: https://skillsregistry.net/skills/myangsun-loc-memory-server  
JSON: https://api.skillsregistry.net/v1/skills/myangsun-loc-memory-server

## Description

Remember user details and preferences across conversations. Organize facts into connected profiles for richer, long-term context. Search, update, and automatically extract locations to keep memories accurate and actionable.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** maps-location
- **Updated:** 2026-04-27

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/Myangsun/loc-memory-server)
- **Repository:** <https://github.com/Myangsun/loc-memory-server>

## 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": "myangsun-loc-memory-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/myangsun-loc-memory-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/myangsun-loc-memory-server/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