# vvriter

> Use this tool when you need to generate articles based on large datasets of social media posts and visual content. The vvriter tool solves the problem of creating written content from vast amounts of unstructured data, such as 50,000 tweets, and combines it with insights from 400 visual artworks. It takes in these large datasets as input and outputs cohesive articles, making it ideal for use cases where automated content generation is required.

Canonical page: https://skillsregistry.net/skills/visualizevalue-vvriter  
JSON: https://api.skillsregistry.net/v1/skills/visualizevalue-vvriter

## Description

MCP server that generates articles from 50,000 tweets and 400 visual artworks.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/vkvkf17ygp)
- **Repository:** <https://github.com/visualizevalue/vvriter>

## 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": "visualizevalue-vvriter"
    }
  }
}
```

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