# AI Vision

> Use this tool when you need to analyze images or videos using AI-powered models, such as Google's Gemini and Vertex AI, to solve problems like content moderation, visual data analysis, and educational applications. It accepts inputs like URLs, local file paths, and base64 data, and provides outputs through three core tools: image analysis, image comparison, and video analysis. Ideal for workflows requiring intelligent understanding of visual media, AI Vision offers flexible deployment options and robust error handling.

Canonical page: https://skillsregistry.net/skills/tan-yong-sheng-ai-vision  
JSON: https://api.skillsregistry.net/v1/skills/tan-yong-sheng-ai-vision

## Description

AI Vision MCP provides AI assistants with powerful image and video analysis capabilities through Google's Gemini and Vertex AI models, supporting both Google AI Studio API keys and Vertex AI service accounts for flexible deployment options. Built by tan-yong-sheng with TypeScript, it offers three core tools: analyze_image for single image analysis, compare_images for multi-image comparison (up to 4 images), and analyze_video for video content analysis, with intelligent file handling that supports URLs, local file paths, and base64 data. The implementation features smart upload strategies that automatically choose between direct API calls for smaller files and cloud storage (Google Cloud Storage for Vertex AI, Files API for Gemini) for larger files, with comprehensive error handling, retry logic, and configurable processing limits, making it valuable for content moderation, visual data analysis, educational applications, and any workflow requiring AI-powered understanding of visual media.

## Trust

- **Trust score (0–1):** 0.61
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** devops-ci
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/tan-yong-sheng-ai-vision)
- **Repository:** <https://github.com/tan-yong-sheng/ai-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": "tan-yong-sheng-ai-vision"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/tan-yong-sheng-ai-vision` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/tan-yong-sheng-ai-vision/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