# recallnest

> recallnest — erinlkolp-recallnest. Use this tool when you need to manage and recall code snippets and AI models in a persistent memory server, solving version control and knowledge retention issues for AI code agents. It accepts git inputs and provides recalled code and model outputs, streamlining AI development workflows. Ideal for use cases requiring collaborative AI model development and persistent memory management.

Canonical page: https://skillsregistry.net/skills/erinlkolp-recallnest  
JSON: https://api.skillsregistry.net/v1/skills/erinlkolp-recallnest

## Description

Forked persistent memory server for AI Code Agents (MCP)

## Trust

- **Trust score (0–1):** 0.79
- **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/erinlkolp/recallnest)

## 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": "erinlkolp-recallnest"
    }
  }
}
```

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