# recall

> recall — pablowinck-recall. Use this tool when you need to efficiently memorize and recall information using flashcards with spaced repetition. It solves problems of knowledge retention and learning by providing a personalized study schedule, taking input from users and AI assistants through MCP, and outputting optimized study materials. Ideal for use in contexts where memorization and recall are crucial, such as language learning or exam preparation.

Canonical page: https://skillsregistry.net/skills/pablowinck-recall  
JSON: https://api.skillsregistry.net/v1/skills/pablowinck-recall

## Description

Free, open-source flashcards with spaced repetition that your AI assistant fills through MCP. https://userecall.org

## Trust

- **Trust score (0–1):** 0.66
- **Verification tier:** scanned
- **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/pablowinck/recall)

## 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": "pablowinck-recall"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/pablowinck-recall` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/pablowinck-recall/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