# Extremis Memory Connector for all AI agents

> Use this tool when you need to enhance AI agents with long-term memory capabilities without requiring extensive pipeline development. The Extremis Memory Connector solves the problem of knowledge retention and recall in AI models, enabling them to learn from past experiences and make more informed decisions. It provides a simple interface for inputting and outputting memories, allowing for seamless integration into existing AI systems.

Canonical page: https://skillsregistry.net/skills/ashwanijha04-extremis  
JSON: https://api.skillsregistry.net/v1/skills/ashwanijha04-extremis

## Description

Give long term memory to your agents without building the RAG pipelines.

## Trust

- **Trust score (0–1):** 0.94
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** devops-ci
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/cnqjpw20kg)
- **Repository:** <https://github.com/ashwanijha04/extremis>

## 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": "ashwanijha04-extremis"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ashwanijha04-extremis` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ashwanijha04-extremis/pull`

---
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