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MCP Veo 3 Video Generation Server

by dayongd1
GitHub
Python
MIT License
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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

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

  • 🖼️ Image-to-Video: Animate static images with motion prompts

  • 🎵 Audio Generation: Native audio generation with Veo 3 models

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

  • 📐 Aspect Ratios: Widescreen (16:9) and portrait (9:16) support

  • ❌ Negative Prompts: Specify what to avoid in generated videos

  • 📁 File Management: List and manage generated videos

  • ⚡ 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

✅

veo-3.0-fast-generate-preview

Optimized for speed and business use

Faster

High

✅

veo-2.0-generate-001

Previous generation model

Medium

Good

❌

📦 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:

  • ❌ Don't use "no" or "don't": "no cars"

  • ✅ 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

🚨 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

📚 Links

License

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

Support

Changelog

v1.0.1

  • 🔧 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

This server cannot be installed

-
security - not tested
A
license - permissive license
-
quality - not tested

How are these scores calculated?

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

Enables video generation from text prompts or images using Google's Veo 3 API. Supports multiple models, audio generation, and various aspect ratios for creating high-quality videos.

  1. Features
    1. Supported Models
      1. 📦 Installation Options
        1. Installation
          1. Option 1: Direct Usage (Recommended)
          2. Option 2: Development Setup
        2. Configuration
          1. Environment Variables
          2. MCP Client Configuration
        3. Available Tools
          1. 1. generate_video
          2. 2. generate_video_from_image
          3. 3. list_generated_videos
          4. 4. get_video_info
        4. Usage Examples
          1. Basic Text-to-Video Generation
          2. Image-to-Video with Negative Prompt
          3. Creative Animation
        5. Prompt Writing Tips
          1. Effective Prompts
          2. Example Prompts
          3. Negative Prompts
        6. Limitations
          1. 🚨 Troubleshooting
            1. Error Handling
              1. Development
                1. Running Tests
                2. Code Formatting
              2. Contributing
                1. 📚 Links
                  1. License
                    1. Support
                      1. Changelog
                        1. v1.0.1
                        2. v1.0.0

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