# Memorised them All

> Use this tool when you need to quickly recall information from a large collection of documents, such as PDFs, Word files, and web pages. Memorised them All solves the problem of manually searching through numerous files by indexing and remembering their contents, allowing you to ask questions and receive answers with cited sources. It takes in various file types as input and outputs relevant information in response to user queries.

Canonical page: https://skillsregistry.net/skills/gru-953-memorised-them-all  
JSON: https://api.skillsregistry.net/v1/skills/gru-953-memorised-them-all

## Description

Imagine you could hand Claude a filing cabinet of your documents and say "remember all of this." Later you just ask questions, and Claude answers from what it remembers — citing which document each fact came from.

That's Memorised them All. It's a small add-on (an MCP server) for Claude Desktop and Claude Code that:

Reads your files — PDFs, Word/Excel/PowerPoint, web pages, images (with OCR), ev

## Trust

- **Trust score (0–1):** 0.47
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-09-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/qnpihqtoo5)
- **Repository:** <https://github.com/GRU-953/MTA_Plugin>

## 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": "gru-953-memorised-them-all"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/gru-953-memorised-them-all` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/gru-953-memorised-them-all/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