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RamboRogers

FAL Image/Video MCP Server

by RamboRogers

vidu_text

Generate high-quality videos from text prompts using FAL AI models, with customizable duration and aspect ratio options.

Instructions

Vidu Q1 - High-quality text-to-video

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesText prompt for video generation
durationNo
aspect_ratioNo16:9

Implementation Reference

  • The handleTextToVideo method that implements the execution logic for the 'vidu_text' tool by calling the FAL API, processing the video output, handling downloads, data URLs, and auto-opening.
    private async handleTextToVideo(args: any, model: any) {
      const { prompt, duration = 5, aspect_ratio = '16:9' } = args;
    
      try {
        // Configure FAL client lazily with query config override
        configureFalClient(this.currentQueryConfig);
        const inputParams: any = { prompt };
        
        if (duration) inputParams.duration = duration;
        if (aspect_ratio) inputParams.aspect_ratio = aspect_ratio;
    
        const result = await fal.subscribe(model.endpoint, { input: inputParams });
        const videoData = result.data as FalVideoResult;
        const videoProcessed = await downloadAndProcessVideo(videoData.video.url, model.id);
    
        return {
          content: [
            {
              type: 'text',
              text: JSON.stringify({
                model: model.name,
                id: model.id,
                endpoint: model.endpoint,
                prompt,
                video: {
                  url: videoData.video.url,
                  localPath: videoProcessed.localPath,
                  ...(videoProcessed.dataUrl && { dataUrl: videoProcessed.dataUrl }),
                  width: videoData.video.width,
                  height: videoData.video.height,
                },
                metadata: inputParams,
                download_path: DOWNLOAD_PATH,
                data_url_settings: {
                  enabled: ENABLE_DATA_URLS,
                  max_size_mb: Math.round(MAX_DATA_URL_SIZE / 1024 / 1024),
                },
                autoopen_settings: {
                  enabled: AUTOOPEN,
                  note: AUTOOPEN ? "Files automatically opened with default application" : "Auto-open disabled"
                },
              }, null, 2),
            },
          ],
        };
      } catch (error) {
        throw new Error(`${model.name} generation failed: ${error}`);
      }
    }
  • src/index.ts:117-117 (registration)
    Registry entry in MODEL_REGISTRY.textToVideo that defines the 'vidu_text' tool ID, endpoint, name, and description used for dynamic tool registration.
    { id: 'vidu_text', endpoint: 'fal-ai/vidu/q1/text-to-video', name: 'Vidu Q1', description: 'High-quality text-to-video' }
  • Dynamic input schema generation for text-to-video tools like 'vidu_text' in generateToolSchema, defining prompt, duration, and aspect_ratio parameters.
    } else if (category === 'textToVideo') {
      baseSchema.inputSchema.properties = {
        prompt: { type: 'string', description: 'Text prompt for video generation' },
        duration: { type: 'number', default: 5, minimum: 1, maximum: 30 },
        aspect_ratio: { type: 'string', enum: ['16:9', '9:16', '1:1', '4:3', '3:4'], default: '16:9' },
      };
      baseSchema.inputSchema.required = ['prompt'];
  • Helper function getModelById used to retrieve the model configuration for 'vidu_text' during tool dispatch.
    // Helper function to get model by ID
    function getModelById(id: string) {
      const allModels = getAllModels();
      return allModels.find(model => model.id === id);
    }
  • Dispatch logic in CallToolRequestSchema handler that routes 'vidu_text' calls to handleTextToVideo based on registry lookup.
      return await this.handleImageGeneration(args, model);
    } else if (MODEL_REGISTRY.textToVideo.find(m => m.id === name)) {
      return await this.handleTextToVideo(args, model);
    } else if (MODEL_REGISTRY.imageToVideo.find(m => m.id === name)) {
      return await this.handleImageToVideo(args, model);

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