Amazon Bedrock MCP Server

Instructions

Implementation Reference

• src/index.ts:182-311 (handler)

  Handler for the generate_image tool. Validates input using GenerateImageSchema, invokes AWS Bedrock Nova model via InvokeModelCommand, processes the response to extract base64 images, and returns MCP-formatted content with images.
  server.setRequestHandler(CallToolRequestSchema, async (request) => { if (request.params.name !== "generate_image") { throw new McpError( ErrorCode.MethodNotFound, `Unknown tool: ${request.params.name}` ); } try { // Validate and parse input const args = GenerateImageSchema.parse(request.params.arguments); server.sendLoggingMessage({ level: "info", data: `Configuration: ${JSON.stringify({ width: args.width, height: args.height, quality: args.quality, numberOfImages: args.numberOfImages, cfgScale: args.cfg_scale, seed: args.seed })}`, }); const progressToken = request.params._meta?.progressToken; server.sendLoggingMessage({ level: "info", data: "Sending request to Bedrock API...", }); const response = await bedrock.send(new InvokeModelCommand({ modelId: NOVA_MODEL_ID, contentType: "application/json", accept: "application/json", body: JSON.stringify({ taskType: GENERATION_TYPES.TEXT_TO_IMAGE, textToImageParams: { text: args.prompt, negativeText: args.negativePrompt || undefined, }, imageGenerationConfig: { numberOfImages: args.numberOfImages, height: args.height, width: args.width, quality: args.quality, cfgScale: args.cfg_scale, seed: args.seed }, }), })); server.sendLoggingMessage({ level: "info", data: "Received response from Bedrock API", }); if (!response.body) { server.sendLoggingMessage({ level: "error", data: "No response body received from Bedrock", }); throw new McpError( ErrorCode.InternalError, "No response body received from Bedrock" ); } const responseBody = JSON.parse(new TextDecoder().decode(response.body)) as BedrockResponse; if (!responseBody.images || responseBody.images.length === 0) { server.sendLoggingMessage({ level: "error", data: "No image data in response", }); throw new McpError( ErrorCode.InternalError, `No image data in response due to ${responseBody.error}.` ); } server.sendLoggingMessage({ level: "info", data: "Successfully generated image", }); // Return the response in the correct MCP format return { content: [ { type: "text", text: `This is the image generated for your request '${args.prompt}'.`, }, ...responseBody.images.map(image => ({ type: "image", data: image as string, mimeType: "image/png", })), { type: "text", text: "This is the end of the image generation.", } ], }; } catch (error) { console.error('Error:', error); // Handle Zod validation errors if (error instanceof z.ZodError) { throw new McpError( ErrorCode.InvalidParams, `Invalid parameters: ${error.errors.map(e => e.message).join(", ")}` ); } // Handle AWS Bedrock errors if (error instanceof Error) { throw new McpError( ErrorCode.InternalError, `Failed to generate image: ${error.message}` ); } // Handle unknown errors throw new McpError( ErrorCode.InternalError, "An unexpected error occurred" ); } });
• src/index.ts:65-97 (schema)

  Zod schema for validating input parameters to the generate_image tool, including prompt, dimensions, quality, etc., with refinements for aspect ratio and pixel count.
  const GenerateImageSchema = z.object({ prompt: z.string().min(1).max(1024, "Prompt must be 1-1024 characters"), negativePrompt: z.string().min(1).max(1024, "Negative prompt must be 1-1024 characters").optional(), width: z.number().int() .min(320, "Width must be at least 320 pixels") .max(4096, "Width must be at most 4096 pixels") .refine(val => val % 16 === 0, "Width must be divisible by 16") .default(1024), height: z.number().int() .min(320, "Height must be at least 320 pixels") .max(4096, "Height must be at most 4096 pixels") .refine(val => val % 16 === 0, "Height must be divisible by 16") .default(1024), quality: z.enum(["standard", "premium"]).default("standard"), cfg_scale: z.number().min(1.1).max(10).default(6.5), seed: z.number().int().min(0).max(858993459).default(12), numberOfImages: z.number().int().min(1).max(5).default(1) }).refine( (data) => { // Check aspect ratio between 1:4 and 4:1 const ratio = data.width / data.height; return ratio >= 0.25 && ratio <= 4; }, "Aspect ratio must be between 1:4 and 4:1" ).refine( (data) => { // Check total pixel count return data.width * data.height < 4194304; }, "Total pixel count must be less than 4,194,304" ); type GenerateImageInput = z.infer<typeof GenerateImageSchema>;
• src/index.ts:124-172 (registration)

  Registration of the generate_image tool in the ListToolsRequestSchema handler, providing name, description, and JSON input schema.
  server.setRequestHandler(ListToolsRequestSchema, async () => { return { tools: [ { name: "generate_image", description: "Generate image(s) using Amazon Nova Canvas model. The returned data is Base64-encoded string that represent each image that was generated.", inputSchema: { type: "object", properties: { prompt: { type: "string", description: "Text description of the image to generate (1-1024 characters)", }, negativePrompt: { type: "string", description: "Optional text description of what to avoid in the image (1-1024 characters)", }, width: { type: "number", description: "Width of the generated image (default: 1024)", }, height: { type: "number", description: "Height of the generated image (default: 1024)", }, quality: { type: "string", enum: ["standard", "premium"], description: "Quality of the generated image (default: standard)", }, cfg_scale: { type: "number", description: "How closely to follow the prompt (1.1-10, default: 6.5)", }, seed: { type: "number", description: "Seed for reproducible generation (0-858993459, default: 12)", }, numberOfImages: { type: "number", description: "Number of images to generate (1-5, default: 1)", }, }, required: ["prompt"], }, }, ], }; });