media-mcp

# media-mcp MCP server for AI-powered media generation using Google Gemini. Generate images, videos, music, and speech directly from your AI agent. ## Features - **Image Generation** — Create and edit images using Gemini's Nano Banana models with support for multiple aspect ratios, resolutions up to 4K, and reference images - **Video Generation** — Generate videos with native audio, dialogue, and sound effects using Veo models (text-to-video, image-to-video, video extension) - **Music Generation** — Create instrumental music with weighted text prompts using Lyria RealTime (genre, instrument, mood control with BPM and scale) - **Speech Generation** — Convert text to speech with voice selection, multi-speaker support, and natural language style control using Gemini TTS ## Installation ### Using uvx (recommended) ```bash uvx media-mcp ``` ### Using pip ```bash pip install media-mcp ``` ### Prerequisites - Python 3.10+ - A [Google Gemini API key](https://aistudio.google.com/apikey) ## Configuration Set your Gemini API key as an environment variable: ```bash export GEMINI_API_KEY="your-gemini-api-key" ``` ### Environment Variables | Variable | Required | Description | |----------|----------|-------------| | `GEMINI_API_KEY` | Yes | Google Gemini API key for authentication | | `MEDIA_OUTPUT_DIR` | No | Directory path for saving generated media files (see below) | ### Output behavior When `MEDIA_OUTPUT_DIR` is set, every generated file is saved to that directory and the tool returns **only the file path** — no binary data is included in the response. This is the recommended setup because MCP messages are stored in the conversation history, and large base64 payloads pollute context and waste tokens. When `MEDIA_OUTPUT_DIR` is **not** set, the server has no filesystem target, so it returns the raw base64-encoded data directly in the response. This works for quick experiments but is not recommended for production use. ## MCP Client Setup ### Claude Deskto…