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MCP Veo 3 Video Generation Server

by dayongd1
OverviewInspectNewSchemaRelated ServersScore
Python
Remote
MIT License
1

MCP Veo 3 Video Generation Server

A Model Context Protocol (MCP) server that provides video generation capabilities using Google's Veo 3 API through the Gemini API. Generate high-quality videos from text prompts or images with realistic motion and audio.

Features

  • ๐ŸŽฌ Text-to-Video: Generate videos from descriptive text prompts

  • ๐Ÿ–ผ๏ธ Image-to-Video: Animate static images with motion prompts

  • ๐ŸŽต Audio Generation: Native audio generation with Veo 3 models

  • ๐ŸŽจ Multiple Models: Support for Veo 3, Veo 3 Fast, and Veo 2

  • ๐Ÿ“ Aspect Ratios: Widescreen (16:9) and portrait (9:16) support

  • โŒ Negative Prompts: Specify what to avoid in generated videos

  • ๐Ÿ“ File Management: List and manage generated videos

  • โšก Async Processing: Non-blocking video generation with progress tracking

Supported Models

Model

Description

Speed

Quality

Audio

veo-3.0-generate-preview

Latest Veo 3 with highest quality

Slower

Highest

โœ…

veo-3.0-fast-generate-preview

Optimized for speed and business use

Faster

High

โœ…

veo-2.0-generate-001

Previous generation model

Medium

Good

โŒ

๐Ÿ“ฆ Installation Options

# Run without installing (recommended) uvx mcp-veo3 --output-dir ~/Videos/Generated # Install globally pip install mcp-veo3 # Development install git clone && cd mcp-veo3 && uv sync

Installation

Option 1: Direct Usage (Recommended)

# No installation needed - run directly with uvx uvx mcp-veo3 --output-dir ~/Videos/Generated

Option 2: Development Setup

  1. Clone this directory:

    git clone https://github.com/dayongd1/mcp-veo3 cd mcp-veo3

  2. Install with uv:

    uv sync

    Or use the automated setup:

    python setup.py

  3. Set up API key:

    • Get your Gemini API key from Google AI Studio

    • Create .env file: cp env_example.txt .env

    • Edit .env and add your GEMINI_API_KEY

    • Or set environment variable: export GEMINI_API_KEY='your_key'

Configuration

Environment Variables

Create a .env file with the following variables:

# Required GEMINI_API_KEY=your_gemini_api_key_here # Optional DEFAULT_OUTPUT_DIR=generated_videos DEFAULT_MODEL=veo-3.0-generate-preview DEFAULT_ASPECT_RATIO=16:9 PERSON_GENERATION=dont_allow POLL_INTERVAL=10 MAX_POLL_TIME=600

MCP Client Configuration

Option 1: Using uvx (Recommended - after PyPI publication)

{ "mcpServers": { "veo3": { "command": "uvx", "args": ["mcp-veo3", "--output-dir", "~/Videos/Generated"], "env": { "GEMINI_API_KEY": "your_api_key_here" } } } }

Option 2: Using uv run (Development)

{ "mcpServers": { "veo3": { "command": "uv", "args": ["run", "--directory", "/path/to/mcp-veo3", "mcp-veo3", "--output-dir", "~/Videos/Generated"], "env": { "GEMINI_API_KEY": "your_api_key_here" } } } }

Option 3: Direct Python

{ "mcpServers": { "veo3": { "command": "python", "args": ["/path/to/mcp-veo3/mcp_veo3.py", "--output-dir", "~/Videos/Generated"], "env": { "GEMINI_API_KEY": "your_api_key_here" } } } }

CLI Arguments:

  • --output-dir (required): Directory to save generated videos

  • --api-key (optional): Gemini API key (overrides environment variable)

Available Tools

1. generate_video

Generate a video from a text prompt.

Parameters:

  • prompt (required): Text description of the video

  • model (optional): Model to use (default: veo-3.0-generate-preview)

  • negative_prompt (optional): What to avoid in the video

  • aspect_ratio (optional): 16:9 or 9:16 (default: 16:9)

  • output_dir (optional): Directory to save videos (default: generated_videos)

Example:

{ "prompt": "A close up of two people staring at a cryptic drawing on a wall, torchlight flickering. A man murmurs, 'This must be it. That's the secret code.' The woman looks at him and whispering excitedly, 'What did you find?'", "model": "veo-3.0-generate-preview", "aspect_ratio": "16:9" }

2. generate_video_from_image

Generate a video from a starting image and motion prompt.

Parameters:

  • prompt (required): Text description of the desired motion/action

  • image_path (required): Path to the starting image file

  • model (optional): Model to use (default: veo-3.0-generate-preview)

  • negative_prompt (optional): What to avoid in the video

  • aspect_ratio (optional): 16:9 or 9:16 (default: 16:9)

  • output_dir (optional): Directory to save videos (default: generated_videos)

Example:

{ "prompt": "The person in the image starts walking forward with a confident stride", "image_path": "./images/person_standing.jpg", "model": "veo-3.0-generate-preview" }

3. list_generated_videos

List all generated videos in the output directory.

Parameters:

  • output_dir (optional): Directory to list videos from (default: generated_videos)

4. get_video_info

Get detailed information about a video file.

Parameters:

  • video_path (required): Path to the video file

Usage Examples

Basic Text-to-Video Generation

# Through MCP client result = await mcp_client.call_tool("generate_video", { "prompt": "A majestic waterfall in a lush forest with sunlight filtering through the trees", "model": "veo-3.0-generate-preview" })

Image-to-Video with Negative Prompt

result = await mcp_client.call_tool("generate_video_from_image", { "prompt": "The ocean waves gently crash against the shore", "image_path": "./beach_scene.jpg", "negative_prompt": "people, buildings, artificial structures", "aspect_ratio": "16:9" })

Creative Animation

result = await mcp_client.call_tool("generate_video", { "prompt": "A stylized animation of a paper airplane flying through a colorful abstract landscape", "model": "veo-3.0-fast-generate-preview", "aspect_ratio": "16:9" })

Prompt Writing Tips

Effective Prompts

  • Be specific: Include details about lighting, mood, camera angles

  • Describe motion: Specify the type of movement you want

  • Set the scene: Include environment and atmospheric details

  • Mention style: Cinematic, realistic, animated, etc.

Example Prompts

Cinematic Realism:

A tracking drone view of a red convertible driving through Palm Springs in the 1970s, warm golden hour sunlight, long shadows, cinematic camera movement

Creative Animation:

A stylized animation of a large oak tree with leaves blowing vigorously in strong wind, peaceful countryside setting, warm lighting

Dialogue Scene:

Close-up of two people having an intense conversation in a dimly lit room, dramatic lighting, one person gesturing emphatically while speaking

Negative Prompts

Describe what you don't want to see:

  • โŒ Don't use "no" or "don't": "no cars"

  • โœ… Do describe unwanted elements: "cars, vehicles, traffic"

Limitations

  • Generation Time: 11 seconds to 6 minutes depending on complexity

  • Video Length: 8 seconds maximum

  • Resolution: 720p output

  • Storage: Videos are stored on Google's servers for 2 days only

  • Regional Restrictions: Person generation defaults to "dont_allow" in EU/UK/CH/MENA

  • Watermarking: All videos include SynthID watermarks

๐Ÿšจ Troubleshooting

"API key not found"

# Set your Gemini API key export GEMINI_API_KEY='your_api_key_here' # Or add to .env file echo "GEMINI_API_KEY=your_api_key_here" >> .env

"Output directory not accessible"

# Ensure the output directory exists and is writable mkdir -p ~/Videos/Generated chmod 755 ~/Videos/Generated

"Video generation timeout"

# Try using the fast model for testing uvx mcp-veo3 --output-dir ~/Videos # Then use: model="veo-3.0-fast-generate-preview"

"Import errors"

# Install/update dependencies uv sync # Or with pip pip install -r requirements.txt

Error Handling

The server handles common errors gracefully:

  • Invalid API Key: Clear error message with setup instructions

  • File Not Found: Validation for image paths in image-to-video

  • Generation Timeout: Configurable timeout with progress updates

  • Model Errors: Fallback error handling with detailed messages

Development

Running Tests

# Install test dependencies pip install pytest pytest-asyncio # Run tests pytest tests/

Code Formatting

# Format code black mcp_veo3.py # Check linting flake8 mcp_veo3.py # Type checking mypy mcp_veo3.py

Contributing

  1. Fork the repository

  2. Create a feature branch

  3. Make your changes

  4. Add tests if applicable

  5. Submit a pull request

๐Ÿ“š Links

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

Changelog

v1.0.1

  • ๐Ÿ”ง API Fix: Updated to match official Veo 3 API specification

  • Removed unsupported parameters: aspect_ratio, negative_prompt, person_generation

  • Simplified API calls: Now using only model and prompt parameters as per official docs

  • Fixed video generation errors: Resolved "unexpected keyword argument" issues

  • Updated documentation: Added notes about current API limitations

v1.0.0

  • Initial release

  • Support for Veo 3, Veo 3 Fast, and Veo 2 models

  • Text-to-video and image-to-video generation

  • FastMCP framework with progress tracking

  • Comprehensive error handling and logging

  • File management utilities

  • uv/uvx support for easy installation

Built with FastMCP | Python 3.10+ | MIT License

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