# io.github.camgitt/memoir

> Use this tool when you need to retain information across multiple coding sessions and machines, providing persistent memory for AI coding tools via MCP. It solves the problem of lost context and data by remembering key information, enabling seamless continuity of work. Ideal for use cases requiring long-term memory and data retention, such as iterative coding and collaborative development.

Canonical page: https://skillsregistry.net/skills/io-github-camgitt-memoir  
JSON: https://api.skillsregistry.net/v1/skills/io-github-camgitt-memoir

## Description

Persistent memory for AI coding tools via MCP. Remembers across sessions and machines.

## Trust

- **Trust score (0–1):** 0.00
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 3.2.2
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-28

## Source

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

## 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-camgitt-memoir"
    }
  }
}
```

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