# veyra-memory

> veyra-memory — aquariosan-veyra-memory. Use this tool when you need to store and retrieve persistent data for AI agents, solving problems of data loss and inconsistency across sessions. It provides read and write functionality, with writes requiring Veyra commit mode, and integrates with git for version control. Ideal for use cases where AI agents require access to shared, persistent memory.

Canonical page: https://skillsregistry.net/skills/aquariosan-veyra-memory  
JSON: https://api.skillsregistry.net/v1/skills/aquariosan-veyra-memory

## Description

Persistent memory for AI agents. Reads free, writes require Veyra commit mode.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/Aquariosan/veyra-memory)

## 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": "aquariosan-veyra-memory"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/aquariosan-veyra-memory` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/aquariosan-veyra-memory/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