# cli

> cli — memcell-ai-cli. Use this tool when you need to enhance AI coding agents with persistent memory and decision recall capabilities. It solves problems of knowledge retention and calibration across coding sessions, supporting cross-vendor compatibility and integration with git. The cli tool provides a robust interface for inputs and outputs, enabling effective outcome calibration via MCP and hooks.

Canonical page: https://skillsregistry.net/skills/memcell-ai-cli  
JSON: https://api.skillsregistry.net/v1/skills/memcell-ai-cli

## Description

Living memory for AI coding agents (Claude Code, Cursor, Copilot, Codex). Cross-vendor persistent memory, decision recall, and outcome calibration via MCP and hooks.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/memcell-ai/cli)

## 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": "memcell-ai-cli"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/memcell-ai-cli` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/memcell-ai-cli/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