# mindkeg-mcp

> mindkeg-mcp — carloluisito-mindkeg-mcp. Use this tool when you need to retain knowledge across AI agent sessions, storing and retrieving learnings for consistent performance. It solves the problem of knowledge loss between sessions, enabling agents to build upon previous experiences. The mindkeg-mcp server accepts atomic learnings as input and provides searched and retrieved knowledge as output, integrating with git for version control.

Canonical page: https://skillsregistry.net/skills/carloluisito-mindkeg-mcp  
JSON: https://api.skillsregistry.net/v1/skills/carloluisito-mindkeg-mcp

## Description

A persistent memory MCP server for AI coding agents — stores, searches, and retrieves atomic learnings so agents retain knowledge across sessions.

## Trust

- **Trust score (0–1):** 0.84
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/carloluisito/mindkeg-mcp)

## 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": "carloluisito-mindkeg-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/carloluisito-mindkeg-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/carloluisito-mindkeg-mcp/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