# emem

> emem — vortx-ai-emem. Use this tool when you need to access a reliable and cite-able record of geographic locations, as it provides a content-addressed and signed memory of every place on Earth, solving problems related to data verification and validation. It takes geographic coordinates as input and outputs verified information about the location. Utilize emem in applications requiring trusted and trustworthy geographic data, such as research, mapping, and urban planning.

Canonical page: https://skillsregistry.net/skills/vortx-ai-emem  
JSON: https://api.skillsregistry.net/v1/skills/vortx-ai-emem

## Description

Cite-able, content-addressed, signed memory of every place on Earth

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-07-17

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/u9ncaux4l6)
- **Repository:** <https://github.com/Vortx-AI/emem>

## 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": "vortx-ai-emem"
    }
  }
}
```

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