# chatdb

> chatdb — svtter-chatdb. Use this tool when you need to record and store information in a lightweight database, providing a simple memory layer for AI models like GPT. It solves problems related to data persistence and retrieval, allowing for efficient storage and querying of data. The chatdb tool takes in user input and outputs stored data, utilizing a SQLite database interface.

Canonical page: https://skillsregistry.net/skills/svtter-chatdb  
JSON: https://api.skillsregistry.net/v1/skills/svtter-chatdb

## Description

A small mcp service to record things in sqlite. A simple GPT memory layer. ;)

## Trust

- **Trust score (0–1):** 0.96
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/Svtter/chatdb)

## 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": "svtter-chatdb"
    }
  }
}
```

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