# vision-mcp

> Use this tool when you need to analyze and describe visual content, as it solves problems related to image understanding and accessibility by taking file paths, URLs, or base64 data as input and generating human-like descriptions of images as output. It is particularly useful in applications where image recognition and interpretation are required, such as content moderation or image categorization. This tool is ideal for use cases where automated image analysis can enhance user experience or facilitate data processing.

Canonical page: https://skillsregistry.net/skills/winton979-vision-mcp  
JSON: https://api.skillsregistry.net/v1/skills/winton979-vision-mcp

## Description

MCP server that provides an analyze_image tool using OpenAI-compatible vision LLMs to describe images from file paths, URLs, or base64 data.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/vpeq9mistr)
- **Repository:** <https://github.com/winton979/vision-mcp>

## 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": "winton979-vision-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/winton979-vision-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/winton979-vision-mcp/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