piotrkandziora/pmind-veo-mcp
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The PMIND Veo MCP Server is an experimental server designed for video generation using Google's Veo AI models through the Gemini API.
PMIND Veo MCP Server
⚠️ Experimental: This MCP server is in an experimental state and may have rough edges. Please report any issues you encounter.
A Python implementation of an MCP (Model Context Protocol) server using FastMCP that provides tools for generating videos with Google's Veo AI models through the Gemini API. This server uses a subprocess-based architecture for reliable long-running video generation tasks with the official google-genai Python SDK.
🎯 Features
Core Capabilities
- Video Generation: Generate videos from text prompts using Veo models
- Image-to-Video: Animate images with Veo 3 models
- Fast Generation: Veo 3 Fast model for speed-optimized video creation
- Subprocess Architecture: Non-blocking video generation with isolated subprocess handling
- Progress Tracking: Real-time status updates via state file monitoring
- Video Downloads: Download completed videos using the official google-genai SDK
- Multiple Generations: Track and manage multiple concurrent video generations
- Process Management: Graceful cancellation and cleanup of generation processes
Installation & Setup
Step 1: Clone the Repository
git clone https://github.com/yourusername/pmind-veo-mcp.git
cd pmind-veo-mcp
Step 2: Install Dependencies
# Install dependencies using uv
uv sync
Step 3: Set Up API Key
- Get a Gemini API key from Google AI Studio
- Create a
.env
file in the project root:
cp .env.example .env
- Edit
.env
and add your configuration:
# Required: Your Gemini API key for Veo access
GEMINI_API_KEY=your_api_key_here
# Required: Default Veo model to use
# Options: veo-2.0-generate-001, veo-3.0-generate-preview, veo-3.0-fast-generate-preview
VEO_MODEL=veo-3.0-generate-preview
# Optional: Configuration directory (default: ~/.pmind-veo-mcp)
# CONFIG_DIR=/path/to/config
Step 4: Configure with Your Client
Add the MCP server to your client's MCP configuration:
{
"mcpServers": {
"pmind-veo": {
"command": "uv",
"args": ["run", "--directory", "/path/to/pmind-veo-mcp", "pmind-veo-mcp"]
}
}
}
Configuration
Required Environment Variables
GEMINI_API_KEY
: Your Gemini API key with video generation accessVEO_MODEL
: Default model (must be full API name):veo-2.0-generate-001
for Veo 2veo-3.0-generate-preview
for Veo 3veo-3.0-fast-generate-preview
for Veo 3 Fast (speed-optimized)
Optional Environment Variables
CONFIG_DIR
: Directory for state files and downloads (default:~/.pmind-veo-mcp
)
MCP Tools Reference
veo_generate_video
- Start video generation with a text promptveo_check_generation
- Check the status of a video generationveo_download_video
- Download a completed videoveo_list_sessions
- List all video generation sessionsveo_cleanup_sessions
- Clean up old generation sessions