# ContextMemory

> ContextMemory — kortexio-contextmemory. Use this tool when you need to augment language models with persistent memory, enabling them to recall and build upon previous interactions and knowledge. ContextMemory solves the problem of transient LLM knowledge by providing a markdown wiki interface for storing and retrieving information. It accepts git-based inputs and outputs formatted knowledge, ideal for use cases requiring continuous learning and memory retention.

Canonical page: https://skillsregistry.net/skills/kortexio-contextmemory  
JSON: https://api.skillsregistry.net/v1/skills/kortexio-contextmemory

## Description

Agentic gateway providing persistent LLM memory via a markdown wiki. Open-source core of Kortexio.

## Trust

- **Trust score (0–1):** 0.64
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** AGPL-3.0
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/Kortexio/ContextMemory)

## 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": "kortexio-contextmemory"
    }
  }
}
```

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