FAL Image/Video MCP Server

Instructions

Implementation Reference

• src/index.ts:495-563 (handler)

  The core handler function for all image generation tools, including stable_diffusion_35. It processes input arguments, calls the FAL API with the specific endpoint, handles the response, downloads/processes images, and returns formatted content.
  private async handleImageGeneration(args: any, model: any) { const { prompt, image_size = 'landscape_4_3', num_inference_steps = 25, guidance_scale = 3.5, num_images = 1, negative_prompt, safety_tolerance, raw, } = args; try { // Configure FAL client lazily with query config override configureFalClient(this.currentQueryConfig); const inputParams: any = { prompt }; // Add common parameters if (image_size) inputParams.image_size = image_size; if (num_images > 1) inputParams.num_images = num_images; // Add model-specific parameters based on model capabilities if (model.id.includes('flux') || model.id.includes('stable_diffusion')) { if (num_inference_steps) inputParams.num_inference_steps = num_inference_steps; if (guidance_scale) inputParams.guidance_scale = guidance_scale; } if ((model.id.includes('stable_diffusion') || model.id === 'ideogram_v3') && negative_prompt) { inputParams.negative_prompt = negative_prompt; } if (model.id.includes('flux_pro') && safety_tolerance) { inputParams.safety_tolerance = safety_tolerance; } if (model.id === 'flux_pro_ultra' && raw !== undefined) { inputParams.raw = raw; } const result = await fal.subscribe(model.endpoint, { input: inputParams }); const imageData = result.data as FalImageResult; const processedImages = await downloadAndProcessImages(imageData.images, model.id); return { content: [ { type: 'text', text: JSON.stringify({ model: model.name, id: model.id, endpoint: model.endpoint, prompt, images: processedImages, 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:100-108 (registration)

  MODEL_REGISTRY definition where stable_diffusion_35 is registered as an image generation model with its FAL endpoint.
  imageGeneration: [ { id: 'imagen4', endpoint: 'fal-ai/imagen4/preview', name: 'Imagen 4', description: 'Google\'s latest text-to-image model' }, { id: 'flux_kontext', endpoint: 'fal-ai/flux-pro/kontext/text-to-image', name: 'FLUX Kontext Pro', description: 'State-of-the-art prompt adherence and typography' }, { id: 'ideogram_v3', endpoint: 'fal-ai/ideogram/v3', name: 'Ideogram V3', description: 'Advanced typography and realistic outputs' }, { id: 'recraft_v3', endpoint: 'fal-ai/recraft/v3/text-to-image', name: 'Recraft V3', description: 'Professional design and illustration' }, { id: 'stable_diffusion_35', endpoint: 'fal-ai/stable-diffusion-v35-large', name: 'Stable Diffusion 3.5 Large', description: 'Improved image quality and performance' }, { id: 'flux_dev', endpoint: 'fal-ai/flux/dev', name: 'FLUX Dev', description: 'High-quality 12B parameter model' }, { id: 'hidream', endpoint: 'fal-ai/hidream-i1-full', name: 'HiDream I1', description: 'High-resolution image generation' }, { id: 'janus', endpoint: 'fal-ai/janus', name: 'Janus', description: 'Multimodal understanding and generation' }
• src/index.ts:357-373 (schema)

  Dynamic schema generation for imageGeneration tools, including specific parameters for stable_diffusion_35 (steps, guidance, negative prompt).
  if (category === 'imageGeneration') { baseSchema.inputSchema.properties = { prompt: { type: 'string', description: 'Text prompt for image generation' }, image_size: { type: 'string', enum: ['square_hd', 'square', 'portrait_4_3', 'portrait_16_9', 'landscape_4_3', 'landscape_16_9'], default: 'landscape_4_3' }, num_images: { type: 'number', default: 1, minimum: 1, maximum: 4 }, }; baseSchema.inputSchema.required = ['prompt']; // Add model-specific parameters if (model.id.includes('flux') || model.id.includes('stable_diffusion')) { baseSchema.inputSchema.properties.num_inference_steps = { type: 'number', default: 25, minimum: 1, maximum: 50 }; baseSchema.inputSchema.properties.guidance_scale = { type: 'number', default: 3.5, minimum: 1, maximum: 20 }; } if (model.id.includes('stable_diffusion') || model.id === 'ideogram_v3') { baseSchema.inputSchema.properties.negative_prompt = { type: 'string', description: 'Negative prompt' }; } } else if (category === 'textToVideo') {
• src/index.ts:467-482 (handler)

  Dispatch logic in CallToolRequestSchema handler that routes stable_diffusion_35 calls to handleImageGeneration.
  const model = getModelById(name); if (!model) { throw new McpError( ErrorCode.MethodNotFound, `Unknown model: ${name}` ); } // Determine category and handle accordingly if (MODEL_REGISTRY.imageGeneration.find(m => m.id === name)) { 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); }
• src/index.ts:140-144 (helper)

  Helper to retrieve model configuration by ID, used in dispatch and handler.
  function getModelById(id: string) { const allModels = getAllModels(); return allModels.find(model => model.id === id); }