Vidu MCP
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Alternatives to Vidu MCP
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Related Servers
AlicenseNot gradedqualityFmaintenanceEnables video generation from text, images, and more through MCP-compatible apps like Claude and Cursor.52MIT- AlicenseAqualityCmaintenanceEnables video and image generation from any MCP client, with support for models like Veo 3.1, Grok Imagine, and Nano Banana, including text-to-video, image-to-video, image generation and editing.4MIT

@vidofy/mcpofficial
AlicenseAqualityBmaintenanceEnables generating images, video, audio, and speech from MCP clients using your own Vidofy account, with access to hundreds of models for text-to-video, image-to-video, image editing, lipsync, text-to-speech, and voice cloning.955 npm2MIT- AlicenseNot gradedqualityBmaintenanceEnables AI agents to browse video production packages, obtain free quotes, start and track productions with budget safeguards, and download finished videos, thumbnails and subtitles from vidia.kr. It also supports account balance checks and asset library lookups through MCP clients such as Claude, Cursor and Codex.MIT
- AlicenseAqualityCmaintenanceEnables AI photo generation, editing, and video creation from MCP-compatible clients like Claude Desktop, Cursor, and Windsurf.811 npmMIT
- AlicenseNot gradedqualityDmaintenanceEnables 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.20 PyPI3MIT
TDQS
Scored across 5 tools
The tools are clearly differentiated by their input types and purposes: single image, multiple reference images, start-end images, template-based, and text-only generation. However, the first three tools have identical descriptions ('Generate a video from a pic and prompt'), which could cause initial confusion until the specific parameters are examined.
All tools follow a consistent 'generate_[input_type]_to_video' naming pattern (e.g., generate_img_to_video, generate_text_to_video). The pattern is logical and predictable, making it easy to understand what each tool does based on its name alone.
With 5 tools, this is well-scoped for a video generation server. Each tool covers a distinct input modality (image, reference images, start-end images, templates, text), providing comprehensive coverage without being overwhelming or sparse.
The tool set provides complete coverage of video generation modalities for this domain: from single images, multiple reference images, start-end sequences, templates, and pure text prompts. There are no obvious gaps in the core functionality, and all tools return consistent outputs (task_id and video_url).