Face Generator MCP Server

Instructions

Implementation Reference

• src/index.ts:98-259 (handler)

  Handler for CallToolRequestSchema that implements generate_face: parses arguments, creates output directory, fetches random face images from thispersondoesnotexist.com, processes with Sharp (resize, apply shapes: square/circle/rounded), saves as PNG files or returns base64 ImageContent, handles multiple counts and errors.
  this.server.setRequestHandler(CallToolRequestSchema, async (request) => { if (request.params.name !== 'generate_face') { throw new Error(`Unknown tool: ${request.params.name}`); } interface GenerateFaceArgs { outputDir: string; fileName?: string; count?: number; width?: number; height?: number; shape?: string; borderRadius?: number; returnImageContent?: boolean; } if (!request.params.arguments) { throw new Error('Arguments are required'); } const args = request.params.arguments as unknown as GenerateFaceArgs; const { outputDir, fileName = `${Date.now()}.jpg`, count = 1, width = 256, height = 256, returnImageContent = false } = args; try { // Create directory if it doesn't exist if (!fs.existsSync(outputDir)) { fs.mkdirSync(outputDir, { recursive: true }); } const sharp = (await import('sharp')).default; const results = []; const imageContents: ImageContent[] = []; for (let i = 0; i < count; i++) { // Fetch image const response = await axios.get('https://thispersondoesnotexist.com', { responseType: 'arraybuffer', }); // Process image let image = sharp(response.data) .resize(width, height); // Apply shape transformations switch (args.shape || 'square') { case 'circle': const radius = Math.min(width, height) / 2; const circleShape = Buffer.from( `<svg><circle cx="${radius}" cy="${radius}" r="${radius}" fill="white" /></svg>` ); image = image.composite([{ input: circleShape, blend: 'dest-in' }]); break; case 'rounded': const borderRadius = args.borderRadius || 32; const roundedShape = Buffer.from( `<svg><rect width="${width}" height="${height}" rx="${borderRadius}" ry="${borderRadius}" fill="white" /></svg>` ); image = image.composite([{ input: roundedShape, blend: 'dest-in' }]); break; } const imageBuffer = await image.png().toBuffer(); const base64Image = imageBuffer.toString('base64'); // Generate unique filename if multiple images // Ensure .png extension const baseName = fileName.replace(/\.(jpg|jpeg|png)$/i, ''); const finalFileName = count > 1 ? `${baseName}_${i}.png` : `${baseName}.png`; // Save image const filePath = path.join(outputDir, finalFileName); await fs.promises.writeFile(filePath, imageBuffer); if (returnImageContent) { imageContents.push({ type: 'image', mimeType: 'image/png', data: base64Image, }); } results.push(filePath); } const content = returnImageContent ? imageContents : [ { type: 'text', text: `Generated ${count} face image(s):\n${results.join('\n')}`, }, ]; return { content, }; } catch (error) { console.error(error); let errorCode = ErrorCode.InternalError; let errorMessage = 'Unknown error occurred'; if (error instanceof axios.AxiosError) { if (error.code === 'ENOTFOUND') { errorCode = ErrorCode.MethodNotFound; errorMessage = 'Failed to fetch image from thispersondoesnotexist.com: Network error.'; } else { errorCode = ErrorCode.InternalError; errorMessage = `Failed to fetch image: ${error.message}`; } } else if (error instanceof Error) { errorMessage = error.message; if (error.message.includes('ENOSPC')) { errorCode = ErrorCode.InternalError; errorMessage = 'No space left on device.'; } else if (error.message.includes('EEXIST')) { errorCode = ErrorCode.InternalError; errorMessage = 'File already exists.'; } else if (error.message.includes('ENOENT')) { errorCode = ErrorCode.InternalError; errorMessage = 'No such file or directory.'; } else if (error.message.includes('Invalid width')) { errorCode = ErrorCode.InvalidParams; errorMessage = 'Invalid width parameter.'; } else if (error.message.includes('Invalid height')) { errorCode = ErrorCode.InvalidParams; errorMessage = 'Invalid height parameter.'; } else if (error.message.includes('Input buffer contains unsupported image format')) { errorCode = ErrorCode.InvalidParams; errorMessage = 'Unsupported image format.'; } } else { errorMessage = String(error); } const result: CallToolResult = { content: [ { type: 'text', text: `Error generating face: ${errorMessage}`, }, ], isError: true, }; return result; } });
• src/index.ts:103-112 (schema)

  TypeScript interface defining the input arguments for generate_face tool, matching the JSON schema.
  interface GenerateFaceArgs { outputDir: string; fileName?: string; count?: number; width?: number; height?: number; shape?: string; borderRadius?: number; returnImageContent?: boolean; }
• src/index.ts:40-92 (schema)

  JSON input schema for generate_face tool, defining parameters with types, descriptions, defaults, constraints (e.g., count 1-10, dimensions 64-1024), required outputDir.
  inputSchema: { type: 'object', properties: { outputDir: { type: 'string', description: 'Directory to save the image', }, fileName: { type: 'string', description: 'Optional file name (defaults to timestamp)', default: `${Date.now()}.png`, }, count: { type: 'number', description: 'Number of images to generate (default: 1)', default: 1, minimum: 1, maximum: 10 }, width: { type: 'number', description: 'Width of the image in pixels (default: 256)', default: 256, minimum: 64, maximum: 1024 }, height: { type: 'number', description: 'Height of the image in pixels (default: 256)', default: 256, minimum: 64, maximum: 1024 }, shape: { type: 'string', description: 'Image shape (square|circle|rounded, default: square)', default: 'square', enum: ['square', 'circle', 'rounded'] }, borderRadius: { type: 'number', description: 'Border radius for rounded shape (default: 32)', default: 32, minimum: 0, maximum: 512 }, returnImageContent: { type: 'boolean', description: 'Return image as base64 encoded content instead of file path (default: false)', default: false } }, required: ['outputDir'],
• src/index.ts:37-94 (registration)

  Registration of generate_face tool in ListToolsRequestSchema handler response, including name, description, and full inputSchema.
  { name: 'generate_face', description: 'Generate and save a human face image', inputSchema: { type: 'object', properties: { outputDir: { type: 'string', description: 'Directory to save the image', }, fileName: { type: 'string', description: 'Optional file name (defaults to timestamp)', default: `${Date.now()}.png`, }, count: { type: 'number', description: 'Number of images to generate (default: 1)', default: 1, minimum: 1, maximum: 10 }, width: { type: 'number', description: 'Width of the image in pixels (default: 256)', default: 256, minimum: 64, maximum: 1024 }, height: { type: 'number', description: 'Height of the image in pixels (default: 256)', default: 256, minimum: 64, maximum: 1024 }, shape: { type: 'string', description: 'Image shape (square|circle|rounded, default: square)', default: 'square', enum: ['square', 'circle', 'rounded'] }, borderRadius: { type: 'number', description: 'Border radius for rounded shape (default: 32)', default: 32, minimum: 0, maximum: 512 }, returnImageContent: { type: 'boolean', description: 'Return image as base64 encoded content instead of file path (default: false)', default: false } }, required: ['outputDir'], }, },