# dbboard

> dbboard — meta-taro-dbboard. Use this tool when you need to manage multiple databases from a single interface, leveraging AI-powered insights and automation. It solves problems of data siloing, manual querying, and limited analytics capabilities, supporting use cases like data exploration, querying, and version control with Git integration. The dbboard tool accepts database connections and query inputs, outputting visualized data, query results, and AI-driven recommendations.

Canonical page: https://skillsregistry.net/skills/meta-taro-dbboard  
JSON: https://api.skillsregistry.net/v1/skills/meta-taro-dbboard

## Description

Modern multi-database desktop client with pluggable AI providers

## Trust

- **Trust score (0–1):** 0.74
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/meta-taro/dbboard)

## 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": "meta-taro-dbboard"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/meta-taro-dbboard` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/meta-taro-dbboard/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