# Memento

> Use this tool when you need to retain and recall knowledge across interactions, leveraging a local-first knowledge graph with hybrid search to solve data consistency and information retrieval problems. Memento accepts various data inputs and outputs relevant information, enabling seamless integration with other AI tools. Ideal for applications requiring persistent memory and efficient knowledge management.

Canonical page: https://skillsregistry.net/skills/io-github-scrypster-memento  
JSON: https://api.skillsregistry.net/v1/skills/io-github-scrypster-memento

## Description

Persistent memory for AI tools. Local-first knowledge graph with hybrid search.

## Trust

- **Trust score (0–1):** 0.76
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 0.1.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-09-28

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.github.scrypster%2Fmemento)
- **Repository:** <https://github.com/scrypster/memento>

## 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": "io-github-scrypster-memento"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/io-github-scrypster-memento` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/io-github-scrypster-memento/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