# .github

> .github — hypermemory-ai-github. Use this tool when you need to enhance your AI's memory and intelligence while maintaining data ownership, leveraging git capabilities to store and manage long-term agentic memory. It solves problems related to data retention and AI knowledge retention, allowing for smarter AI interactions. Ideal for use cases where data control and AI intelligence are crucial, with inputs of git-based data storage and outputs of improved AI decision-making.

Canonical page: https://skillsregistry.net/skills/hypermemory-ai-github  
JSON: https://api.skillsregistry.net/v1/skills/hypermemory-ai-github

## Description

Long-term agentic memory that make your AI smarter while you own your data.

## Trust

- **Trust score (0–1):** 0.97
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## 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/hypermemory-ai/.github)

## 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": "hypermemory-ai-github"
    }
  }
}
```

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