Veo MCP Integration Guide
MCP (Model Context Protocol) is a model context protocol launched by Anthropic that allows AI models (such as Claude, GPT, etc.) to call external tools through a standardized interface. With the Veo MCP Server provided by 费思量-API, you can directly use Google Veo to generate AI videos within AI clients like Claude Desktop, VS Code, Cursor, and more.
¶ Feature Overview
Veo MCP Server provides the following core features:
- Text-to-Video — Generate high-quality videos from text prompts
- Image-to-Video — Generate videos based on images
- Multi-Model Support — Supports models such as veo3, veo2, veo31-fast-ingredients, etc.
- Multiple Resolutions — Supports output formats including 4K, 1080p, GIF, etc.
- Multiple Aspect Ratios — Supports ratios such as 16:9, 9:16, etc.
- 1080p Upgrade — Upgrade already generated videos to 1080p
- Task Query — Monitor generation progress and retrieve results
¶ Prerequisites
Before use, you need to obtain an 费思量-API API Token:
- Register or log in to the 费思量-API Platform
- Go to the Veo Videos API page
- Click "Acquire" to get your API Token (first-time applicants receive free credits)
¶ Installation and Configuration
¶ Method 1: pip Installation (Recommended)
pip install mcp-veo
¶ Method 2: Source Installation
git clone https://github.com/AceDataCloud/VeoMCP.git
cd VeoMCP
pip install -e .
After installation, you can start the service using the mcp-veo command.
¶ Using in Claude Desktop
Edit the Claude Desktop configuration file:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
Add the following configuration:
{
"mcpServers": {
"veo": {
"command": "mcp-veo",
"env": {
"ACEDATACLOUD_API_TOKEN": "your API Token"
}
}
}
}
If using uvx (no need to pre-install packages):
{
"mcpServers": {
"veo": {
"command": "uvx",
"args": ["mcp-veo"],
"env": {
"ACEDATACLOUD_API_TOKEN": "your API Token"
}
}
}
}
After saving the configuration, restart Claude Desktop to use Veo-related tools in conversations.
¶ Using in VS Code / Cursor
Create .vscode/mcp.json in the project root directory:
{
"servers": {
"veo": {
"command": "mcp-veo",
"env": {
"ACEDATACLOUD_API_TOKEN": "your API Token"
}
}
}
}
Or use uvx:
{
"servers": {
"veo": {
"command": "uvx",
"args": ["mcp-veo"],
"env": {
"ACEDATACLOUD_API_TOKEN": "your API Token"
}
}
}
}
¶ Available Tools
| Tool Name | Description |
|---|---|
veo_text_to_video |
Generate video from text prompts |
veo_image_to_video |
Generate video based on images |
veo_get_1080p |
Upgrade video to 1080p |
veo_get_task |
Query the status of a single task |
veo_get_tasks_batch |
Batch query task statuses |
¶ Usage Examples
After configuration, you can directly invoke these features in AI clients using natural language, for example:
- "Help me generate a starry sky time-lapse video with Veo"
- "Generate a 4K video from this landscape photo"
- "Create a vertical 9:16 short video"
- "Upgrade this video to 1080p"
¶ More Information
- GitHub Repository: 费思量-API/VeoMCP
- PyPI Package: mcp-veo
- API Documentation: Veo Video Generation API