# vizro-mcp

> Use this tool when you need to visualize and analyze complex data, solve problems related to data interpretation, and gain insights from large datasets. It provides an interface for inputting data and outputs visual representations and patterns, enabling informed decision-making. Ideal for use cases where data-driven understanding is crucial, such as business intelligence, research, and data science applications.

Canonical page: https://skillsregistry.net/skills/mckinsey-vizro  
JSON: https://api.skillsregistry.net/v1/skills/mckinsey-vizro

## Description

Vizro is a low-code toolkit for building high-quality data visualization apps.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-08-21

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/lvw130aakq)
- **Repository:** <https://github.com/mckinsey/vizro>

## 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": "mckinsey-vizro"
    }
  }
}
```

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