# ai-eyes-mcp

> ai-eyes-mcp — mcp-tool-shop-org-ai-eyes-mcp. Use this tool when you need to evaluate the accuracy of image-text pairs or require honest image judgment. The ai-eyes-mcp tool solves problems related to image understanding and validation, providing a reliable assessment via SigLIP2 on a pinned model revision. It takes an image-text pair as input and outputs a score along with the weights that produced the score, abstaining if uncertain.

Canonical page: https://skillsregistry.net/skills/mcp-tool-shop-org-ai-eyes-mcp  
JSON: https://api.skillsregistry.net/v1/skills/mcp-tool-shop-org-ai-eyes-mcp

## Description

Grounded visual evaluator MCP server — honest image judgment via SigLIP2 on a pinned model revision. Measures one image-text pair, names the weights that produced the score, and abstains rather than guessing.

## Trust

- **Trust score (0–1):** 0.87
- **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/mcp-tool-shop-org/ai-eyes-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": "mcp-tool-shop-org-ai-eyes-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/mcp-tool-shop-org-ai-eyes-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/mcp-tool-shop-org-ai-eyes-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