What runtime and dependencies are required?
Node.js 14+, Playwright for browser automation, and a Gemini API key for AI vision analysis.
@samihalawa
基本情報
A Model Context Protocol server for AI vision analysis using Gemini Vision API
ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
An MCP server that provides AI-powered visual analysis capabilities for Claude and other MCP-compatible AI assistants. It captures website screenshots, analyzes UI elements and layouts, reads and modifies files line-specifically, and generates comprehensive UI/UX reports while maintaining context across multiple analysis steps.
Clone the repository, install dependencies with npm install, build with npm run build, then start with npm start. Configure the server in your MCP config by specifying the node command, path to build/index.js, and setting the GEMINI_API_KEY environment variable. Use tools like screenshot_url, analyze_screen, read_file, modify_file, and generate_report to interact with the server.
Node.js 14+, Playwright for browser automation, and a Gemini API key for AI vision analysis.
Add a JSON entry to your MCP config with the correct node path, server build path, set `GEMINI_API_KEY`, and optionally configure port 3005.
`screenshot_url`, `analyze_screen`, `read_file`, `modify_file`, and `generate_report`.
Yes, set the `fullPage` parameter to `true` when using `screenshot_url`; it also supports waiting for a CSS selector or a custom delay.
Yes, the `screenshot_url` tool accepts local URLs such as `http://localhost:4999`.

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