# Memento

> Use this tool when you need to store and retrieve notes for AI assistants, leveraging BM25 search for efficient information retrieval from local JSONL files. It solves problems of knowledge retention and recall, enabling AI agents to learn from past interactions and provide more accurate responses. Ideal for use cases requiring persistent memory and fast search functionality in AI-powered applications.

Canonical page: https://skillsregistry.net/skills/kotrotsos-memento-core  
JSON: https://api.skillsregistry.net/v1/skills/kotrotsos-memento-core

## Description

A persistent memory MCP server for AI assistants, storing and retrieving notes using local JSONL files with BM25 search.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/tiwrizqyu6)
- **Repository:** <https://github.com/Kotrotsos/memento-core>

## 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": "kotrotsos-memento-core"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/kotrotsos-memento-core` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/kotrotsos-memento-core/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