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Why this server?
Enables LLMs to perform web browsing tasks, take screenshots, and execute JavaScript using Puppeteer for browser automation, which could be useful for testing and interacting with Three.js games.
Why this server?
Enables AI agents to control web browsers via a standardized interface for operations like launching, interacting with, and closing browsers, potentially useful for automated testing or demoing of Three.js games.
Why this server?
Allows LLMs to execute Python code in a specified Conda environment, enabling access to necessary libraries and dependencies for efficient code execution related to Three.js or game development tooling.
Why this server?
Provides a Model Context Protocol (MCP) server that exposes MiniZinc constraint solving capabilities to Large Language Models.
Why this server?
Integrates MATLAB with AI to execute code, generate scripts from natural language, and access MATLAB documentation seamlessly, providing a means to generate models or simulations usable in Three.js.
Why this server?
A server that integrates Flux's advanced image generation and manipulation features into AI coding assistants, enabling seamless text-to-image and image control workflows in IDEs like Cursor and Windsurf.
Why this server?
Utilizes Gemini API and Google Search to generate answers based on the latest information for user queries, potentially helping to find up-to-date Three.js documentation or code snippets.
Why this server?
Enables capture screenshots of web pages and local HTML files through a simple MCP tool interface using Puppeteer with configurable options for dimensions and output paths.
Why this server?
Helps AI read GitHub repository structure and important files. Prompt it with "read https://github.com/adhikasp/mcp-git-ingest and determine how the code technically works".