TensorsLab MCP Server
Enables AI-powered image and video generation through the TensorsLab API using models like SeeDream and SeeDance. It supports tasks such as creating high-resolution media from text prompts, image-to-video conversion, and monitoring generation status.
README
TensorsLab MCP Server
A Model Context Protocol (MCP) server that provides tools for generating AI images and videos using the TensorsLab API.
Features
Image Generation Tools
- generate_image_v45 - SeeDream V4.5 (highest quality, recommended)
- generate_image_v4 - SeeDream V4 (faster generation)
- check_image_task_status - Check image generation status
- delete_image_tasks - Delete image tasks
Video Generation Tools
- generate_video_v2 - SeeDance V2 (latest, up to 15s, 1440p)
- generate_video_v15pro - SeeDance V1.5 Pro (high quality)
- generate_video_fast - SeeDance V1 Fast (quick previews)
- check_video_task_status - Check video generation status
- delete_video_tasks - Delete video tasks
Installation
1. Install Dependencies
cd mcp/tensorslab-mcp-server
npm install
2. Build the Project
npm run build
Configuration
Getting Your API Key
- Visit https://test.tensorai.tensorslab.com/
- Sign up or log in
- Navigate to API settings
- Copy your API key
Claude Desktop Configuration
Add the following to your Claude Desktop config file:
Windows: %APPDATA%\Claude\claude_desktop_config.json
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
{
"mcpServers": {
"tensorslab": {
"command": "node",
"args": ["tensorslab-mcp-server/dist/index.js"],
"env": {
"TENSORSLAB_API_KEY": "your-api-key-here"
}
}
}
}
Important: Replace your-api-key-here with your actual TensorsLab API key and update the path if needed.
Usage
Image Generation
// Generate an image with SeeDream V4.5
await generate_image_v45({
prompt: "A beautiful sunset over mountains",
batchSize: 2,
resolution: "16:9"
})
Video Generation
// Generate a video with SeeDance V2
await generate_video_v2({
prompt: "A drone flying over a forest",
ratio: "16:9",
duration: 10,
resolution: "1080p"
})
Tool Parameters Reference
Image Generation (SeeDream V4.5)
| Parameter | Type | Required | Description |
|---|---|---|---|
| prompt | string | Yes | Text description of the image |
| batchSize | number | No | 1-15 images (default: 1) |
| resolution | string | No | 9:16, 16:9, 3:4, 4:3, 1:1, 2:3, 3:2, 2K, 4K, or WxH |
| imageUrl | string | No | Source image URL for image-to-image |
| seed | number | No | Random seed for reproducibility |
| promptExtend | boolean | No | Enable prompt enhancement (default: true) |
Video Generation (SeeDance V2)
| Parameter | Type | Required | Description |
|---|---|---|---|
| prompt | string | Yes | Text description of the video |
| ratio | string | No | 9:16 (vertical) or 16:9 (horizontal) |
| duration | number | No | 5-15 seconds (default: 5) |
| resolution | string | No | 480p, 720p, 1080p, or 1440p |
| fps | string | No | Frame rate (default: 24) |
| imageUrl | string | No | Source image URL for image-to-video |
| generateAudio | boolean | No | Generate audio (default: false) |
| returnLastFrame | boolean | No | Return last frame as image |
| seed | number | No | Random seed for reproducibility |
Development
Run in Development Mode
npm run dev
Run with MCP Inspector
npm run inspector
Build for Production
npm run build
npm start
Project Structure
tensorslab-mcp-server/
├── src/
│ ├── index.ts # Main MCP server with tool registrations
│ ├── api.ts # TensorsLab API client
│ └── types.ts # TypeScript type definitions
├── dist/ # Compiled JavaScript (generated)
├── package.json
├── tsconfig.json
└── README.md
Troubleshooting
"TENSORSLAB_API_KEY environment variable is required"
- Make sure you set the API key in your Claude Desktop config or environment
"Insufficient credits"
- Top up your balance at https://test.tensorai.tensorslab.com/
Task timeout
- Large videos may take longer. Use
check_video_task_statusto poll manually - Image tasks timeout after 3 minutes, video tasks after 5 minutes
Module not found errors
- Run
npm installto ensure all dependencies are installed - Run
npm run buildto compile TypeScript
API Reference
For complete API documentation, see:
License
MIT
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。