{
  "markdown": "# Gemini Media Generation Extension\n\nThis project implements a Gemini CLI Extension (using the Model Context Protocol) that enables AI assistants to generate media using Google Cloud Vertex AI models.\n\n## Purpose\n\nThe extension exposes tools that allow the Gemini CLI to generate high-quality images and videos directly from text prompts or input images. It acts as a bridge between the CLI and Google's generative AI models on Vertex AI.\n\n## Tools\n\n### `nanobanana_generate`\nGenerates images based on a text prompt.\n- **Backend**: Vertex AI (default model: `gemini-2.5-flash-image`).\n- **Features**: Supports text-to-image and image-to-image generation.\n\n### `veo_generate_video`\nGenerates videos based on a text prompt.\n- **Backend**: Vertex AI (default model: `veo-3.1-fast-generate-preview`).\n- **Features**: Supports text-to-video and image-to-video generation.\n\n## Configuration\n\nThe extension requires access to a Google Cloud project with Vertex AI enabled.\n\nCreate a `.env` file in the project root with the following variables:\n\n```env\nVERTEXAI_PROJECT=your-google-cloud-project-id\nVERTEXAI_LOCATION=us-central1\n# Optional Logging Configuration\nLOG_LEVEL=INFO\nLOG_FILE=gemini_media_gen.log\n```\n\n## Install the Extension\n\n```bash\ngemini extensions install https://github.com/rubans/gemini-media-generation.git\n```\n\n## Usage\n\n### `nanobanana_generate`\n```\nGenerate an image of a bouncing tennis ball\n```\n### `veo_generate_video`\n```\nGenerate a video of a bouncing tennis ball  \n```\n\n## Running MCP Server\nAdd MCP Server\n```\ngemini mcp add \"Gemini Media MCP\" uv run --with fastmcp --with-requirements mcp\\\\requirements.txt fastmcp run mcp\\\\servers\\\\gemini_media_gen.py\n```\nRemove MCP Server\n```\ngemini mcp remove \"Gemini Media MCP\"\n```",
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  "repo_slug": "rubans/gemini-media-generation",
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