# io.github.umitkavala/mindpm

> Use this tool when you need to retain project context and knowledge for large language models (LLMs) to avoid redundant explanations. It solves the problem of knowledge loss between interactions by storing project information in a SQLite database. This tool is ideal for ongoing projects that require LLMs to recall previous conversations and context, providing a persistent memory interface for input and output.

Canonical page: https://skillsregistry.net/skills/io-github-umitkavala-mindpm  
JSON: https://api.skillsregistry.net/v1/skills/io-github-umitkavala-mindpm

## Description

Persistent project memory for LLMs via SQLite. Never re-explain your project again.

## Trust

- **Trust score (0–1):** 0.90
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.2.24
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-19

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.github.umitkavala%2Fmindpm)
- **Repository:** <https://github.com/umitkavala/mindpm>

## 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": "io-github-umitkavala-mindpm"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/io-github-umitkavala-mindpm` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/io-github-umitkavala-mindpm/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