# MCP-memento

> MCP-memento — caiowilson-mcp-memento. Use this tool when you need to provide AI agents with a durable and local repository memory, enabling fast semantic code context and version control through git integration. It solves problems related to data persistence and code understanding, allowing agents to access and build upon previous knowledge. Ideal for use cases requiring reliable and efficient code management and retrieval.

Canonical page: https://skillsregistry.net/skills/caiowilson-mcp-memento  
JSON: https://api.skillsregistry.net/v1/skills/caiowilson-mcp-memento

## Description

Local-first MCP server that gives AI agents durable repo memory and fast semantic code context.

## Trust

- **Trust score (0–1):** 0.75
- **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/caiowilson/MCP-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": "caiowilson-mcp-memento"
    }
  }
}
```

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