# OpenMemory

> OpenMemory — user-anto-openmemory. Use this tool when you need to enhance the context memory of large language models (LLMs) with customizable memory sources, solving problems of limited contextual understanding and enabling more accurate responses. OpenMemory allows you to integrate your chosen LLM with the memory of your choice, providing flexible inputs and outputs. Ideal for use cases where contextual memory is crucial, such as conversational AI, language translation, and text summarization.

Canonical page: https://skillsregistry.net/skills/user-anto-openmemory  
JSON: https://api.skillsregistry.net/v1/skills/user-anto-openmemory

## Description

Democratizing Context Memory for LLMs. Use the LLM of your choice on the memory of your choice.

## Trust

- **Trust score (0–1):** 0.80
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/user-anto/OpenMemory)

## 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": "user-anto-openmemory"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/user-anto-openmemory` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/user-anto-openmemory/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