# memory-mcp

> memory-mcp — o-kasian-memory-mcp. Use this tool when you need to efficiently manage and compact memory logs, solving issues of memory bloat and disorganization. It provides a simple interface for logging and compacting memory, accepting input from various sources and outputting optimized logs. Ideal for use cases where memory management is crucial, such as in systems with limited resources or high-performance applications.

Canonical page: https://skillsregistry.net/skills/o-kasian-memory-mcp  
JSON: https://api.skillsregistry.net/v1/skills/o-kasian-memory-mcp

## Description

Simple MCP for logging and compacting the memory

## Trust

- **Trust score (0–1):** 0.95
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/o-kasian/memory-mcp)

## 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": "o-kasian-memory-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/o-kasian-memory-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/o-kasian-memory-mcp/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