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 standardized interfaces. With the Veo MCP Server provided by AceData Cloud, you can directly use Google Veo to generate AI videos in AI clients like Claude Desktop, VS Code, Cursor, etc.Documentation Index
Fetch the complete documentation index at: https://docs.acedata.cloud/llms.txt
Use this file to discover all available pages before exploring further.
Feature Overview
The Veo MCP Server provides the following core functionalities:- Text to Video Generation — Generate high-quality videos from text prompts
- Image to Video Generation — Generate videos based on images
- Multi-Model Support — Supports models like veo3, veo2, veo31-fast-ingredient, etc.
- Multiple Resolutions — Supports output formats like 4K, 1080p, GIF, etc.
- Various Aspect Ratios — Supports ratios like 16:9, 9:16, etc.
- 1080p Upgrade — Upgrade generated videos to 1080p
- Task Querying — Monitor generation progress and obtain results
Prerequisites
Before using, you need to obtain an AceData Cloud API Token:- Register or log in to the AceData Cloud platform
- Go to the Veo Videos API page
- Click “Acquire” to get the API Token (first-time applicants receive free credits)
Installation Configuration
Method 1: pip Installation (Recommended)
Method 2: Source Installation
mcp-veo command to start the service.
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
uvx (no need to install the package in advance):
Using in VS Code / Cursor
Create a.vscode/mcp.json in the project root directory:
uvx:
Available Tools List
| 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 status of a single task |
veo_get_tasks_batch | Batch query task statuses |
Usage Examples
After configuration, you can directly call these functions in the AI client using natural language, for example:- “Help me generate a time-lapse video of the starry sky using 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: AceDataCloud/MCPVeo
- PyPI Package: mcp-veo
- API Documentation: Veo Video Generation API

