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Gemini Vision MCP Server

AI & MLLow Risk10.0MCP RegistryLocalRemote
Free

Server data from the Official MCP Registry

Analyze images and videos with Gemini to get fast, reliable visual insights. Handle content from U…

About

Analyze images and videos with Gemini to get fast, reliable visual insights. Handle content from U…

Remote endpoints: streamable-http: https://server.smithery.ai/@Artin0123/gemini-image-mcp-server/mcp

Security Report

10.0
Low Risk10.0Low Risk

Valid MCP server (2 strong, 2 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.

7 files analyzed · No issues found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

HTTP Network Access

Connects to external APIs or services over the internet.

file_system

Check that this permission is expected for this type of plugin.

env_vars

Check that this permission is expected for this type of plugin.

How to Install & Connect

Available as Local & Remote

This plugin can run on your machine or connect to a hosted endpoint. during install.

Documentation

View on GitHub

From the project's GitHub README.

image-mcp-server-gemini

smithery badge

This is remote server, use local version for local images and videos.

Features

  • Analyze one or more image URLs with a single tool call.
  • Analyze YouTube videos without downloading files locally.
  • Supply an API key and optionally override the Gemini model via environment variables.
  • File size limit: Images are limited to 16 MB to ensure fast processing.
  • YouTube videos: No size limit as they are streamed directly by Gemini API.

Installation

Installing via Smithery

Install the server in Claude Desktop:

npx -y @smithery/cli install @Artin0123/gemini-image-mcp-server --client claude

Manual Installation

# Clone the repository
git clone https://github.com/Artin0123/gemini-vision-mcp.git
cd gemini-vision-mcp

# Install dependencies
npm install

# Compile TypeScript to dist/
npm run build

Configuration

Create a Gemini API key in Google AI Studio and provide GEMINI_API_KEY to the server.

{
  "mcpServers": {
    "gemini-media": {
      "command": "node",
      "args": ["/absolute/path/to/gemini-vision-mcp/dist/index.js"],
      "env": {
        "GEMINI_API_KEY": "your_api_key_here",
        "GEMINI_MODEL": "models/gemini-flash-lite-latest"
      }
    }
  }
}

If no key is supplied, the server can still start (handy for automated scans), but any tool invocation will return a configuration error until a valid API key is configured.

Model override

The server defaults to models/gemini-flash-lite-latest. Override it by either:

Setting the GEMINI_MODEL environment variable, or Providing modelName in the Smithery/SDK configuration schema.

Available tools

  • analyze_image: Analyze one or more image URLs. Maximum file size: 16 MB per image.
  • analyze_youtube_video: Analyze a YouTube video from URL. No size limit.

Image URLs are downloaded and processed with a 16 MB size limit to ensure fast response times. Files exceeding this limit will result in an error message indicating the actual file size.

YouTube videos are streamed directly by Gemini API without downloading, so there is no size restriction.

Prompt examples

Please analyze this product photo: https://teimg-bgr.pages.dev/file/mvYT6KeF.webp
Extract the main talking points from this clip: https://www.youtube.com/watch?v=dQw4w9WgXcQ

Development

npm install
npm test
npm run build

The test suite exercises URL forwarding, MIME handling, and configuration fallbacks.

License

MIT

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