Together AI Image MCP Server

Instructions

Implementation Reference

• src/index.ts:141-275 (handler)

  The CallToolRequestSchema handler implementing the generate_image tool: validates args, calls Together AI API to generate images, processes/resizes with sharp, saves to specified directory, returns file paths.
  this.server.setRequestHandler(CallToolRequestSchema, async (request) => { if (request.params.name !== 'generate_image') { throw new McpError( ErrorCode.MethodNotFound, `Unknown tool: ${request.params.name}` ); } if (!request.params.arguments || !isValidGenerateImageArgs(request.params.arguments)) { throw new McpError( ErrorCode.InvalidParams, 'Invalid generate_image arguments' ); } try { const args = request.params.arguments as GenerateImageArgs; // Get requested dimensions const requestWidth = args.width || 1024; const requestHeight = args.height || 768; // Ensure dimensions are at least 256 pixels for the API request const apiWidth = Math.max(256, requestWidth); const apiHeight = Math.max(256, requestHeight); const response = await this.together.images.create({ model: args.model || 'black-forest-labs/FLUX.1.1-pro', prompt: args.prompt, width: apiWidth, height: apiHeight, steps: args.steps || 28, n: args.n || 1, response_format: 'base64', }); // Use provided output directory or default to 'output' const outputDir = args.outputDir ? path.resolve(args.outputDir) : path.join(process.cwd(), 'output'); // Create output directory if it doesn't exist if (!fs.existsSync(outputDir)) { fs.mkdirSync(outputDir, { recursive: true }); } // Process each generated image const results = await Promise.all(response.data.map(async (result: any, index: number) => { const imageData = result.b64_json; let buffer = Buffer.from(imageData, 'base64'); // Only resize if we need to scale down to match requested dimensions if (requestWidth < 256 || requestHeight < 256) { const metadata = await sharp(buffer).metadata(); const originalWidth = metadata.width || 0; const originalHeight = metadata.height || 0; // Calculate target dimensions maintaining aspect ratio const aspectRatio = originalWidth / originalHeight; let targetWidth = requestWidth; let targetHeight = requestHeight; if (requestWidth < 256) { targetWidth = requestWidth; targetHeight = Math.round(requestWidth / aspectRatio); } if (requestHeight < 256) { targetHeight = requestHeight; targetWidth = Math.round(requestHeight * aspectRatio); } // Resize to match requested dimensions buffer = await sharp(buffer) .resize(targetWidth, targetHeight, { fit: 'contain', background: { r: 255, g: 255, b: 255, alpha: 1 } }) .toBuffer(); } // Save image with timestamp and index const timestamp = new Date().getTime(); const format = args.format || 'png'; const filename = `image_${timestamp}_${index}.${format}`; const filepath = path.join(outputDir, filename); let sharpInstance = sharp(buffer); switch (format) { case 'png': await sharpInstance.png().toFile(filepath); break; case 'jpg': await sharpInstance.jpeg({ quality: 90 }).toFile(filepath); break; case 'svg': // For SVG, we'll need to trace the bitmap to create a vector await sharpInstance .png() .toFile(filepath.replace('.svg', '.png')); // Note: Actual SVG conversion would require additional processing // Consider using potrace or similar library for proper SVG conversion console.warn('SVG output is not fully supported yet'); break; } return { ...result, filepath, filename, dimensions: { original: { width: apiWidth, height: apiHeight }, final: await sharp(filepath).metadata().then(m => ({ width: m.width, height: m.height })) } }; })); return { content: [ { type: 'text', text: JSON.stringify(results, null, 2), }, ], }; } catch (error: any) { console.error('Together AI API error:', error); throw new McpError( ErrorCode.InternalError, `Image generation failed: ${error?.message || 'Unknown error'}` ); } });
• src/index.ts:79-137 (registration)

  Registration of the generate_image tool in the ListToolsRequestSchema response, including name, description, uiSchema, and detailed inputSchema.
  name: 'generate_image', description: 'Generate an image using Together AI', uiSchema: { format: { "ui:widget": "select", "ui:options": { label: "Image Format", position: "above-chat" } } }, inputSchema: { type: 'object', properties: { prompt: { type: 'string', description: 'Text description of the image to generate', }, model: { type: 'string', description: 'Model to use for generation', default: 'black-forest-labs/FLUX.1.1-pro', }, width: { type: 'number', description: 'Image width in pixels', default: 1024, }, height: { type: 'number', description: 'Image height in pixels', default: 768, }, steps: { type: 'number', description: 'Number of inference steps', default: 28, }, n: { type: 'number', description: 'Number of images to generate', default: 1, }, outputDir: { type: 'string', description: 'Full absolute path where images will be saved (e.g., /Users/username/Projects/myapp/src/assets)', pattern: '^/', examples: ['/Users/asanstefanski/Private Projekte/democline/src/assets'], }, format: { type: 'string', enum: ['png', 'jpg', 'svg'], description: 'Output format for the generated images', default: 'png', }, }, required: ['prompt'], }, },
• src/index.ts:90-136 (schema)

  Detailed input schema for generate_image tool parameters including prompt (required), model, dimensions, steps, number of images, output directory, and format.
  inputSchema: { type: 'object', properties: { prompt: { type: 'string', description: 'Text description of the image to generate', }, model: { type: 'string', description: 'Model to use for generation', default: 'black-forest-labs/FLUX.1.1-pro', }, width: { type: 'number', description: 'Image width in pixels', default: 1024, }, height: { type: 'number', description: 'Image height in pixels', default: 768, }, steps: { type: 'number', description: 'Number of inference steps', default: 28, }, n: { type: 'number', description: 'Number of images to generate', default: 1, }, outputDir: { type: 'string', description: 'Full absolute path where images will be saved (e.g., /Users/username/Projects/myapp/src/assets)', pattern: '^/', examples: ['/Users/asanstefanski/Private Projekte/democline/src/assets'], }, format: { type: 'string', enum: ['png', 'jpg', 'svg'], description: 'Output format for the generated images', default: 'png', }, }, required: ['prompt'], },
• src/index.ts:20-29 (schema)

  TypeScript interface defining the expected arguments for generate_image.
  interface GenerateImageArgs { prompt: string; model?: string; width?: number; height?: number; steps?: number; n?: number; outputDir?: string; format?: 'png' | 'jpg' | 'svg'; }
• src/index.ts:31-44 (helper)

  Type guard function to validate generate_image arguments matching GenerateImageArgs interface.
  const isValidGenerateImageArgs = (args: any): args is GenerateImageArgs => { return ( typeof args === 'object' && args !== null && typeof args.prompt === 'string' && (args.model === undefined || typeof args.model === 'string') && (args.width === undefined || typeof args.width === 'number') && (args.height === undefined || typeof args.height === 'number') && (args.steps === undefined || typeof args.steps === 'number') && (args.n === undefined || typeof args.n === 'number') && (args.outputDir === undefined || typeof args.outputDir === 'string') && (args.format === undefined || ['png', 'jpg', 'svg'].includes(args.format)) ); };