GeminiMcpServer

Implementation Reference

• server.js:25-61 (handler)

  The core handler function that generates images using the Google Generative AI Gemini model. It processes the prompt, calls the image generation model, extracts the inline image data, and returns it in the expected MCP format. Handles errors by returning a text error message.

  async (params) => {
    const prompt = params.prompt || "rendered image of fly pig";
    const outputFormat = params.outputFormat || "png";
  
    try {
      // Initialize gemini-2.0-flash-exp-image-generation model
      const model = genAI.getGenerativeModel({
        model: "gemini-2.0-flash-exp-image-generation",
        generationConfig: {
            responseModalities: ['Text', 'Image'],
        },
      });
  
      // Generate the image
      const result = await model.generateContent(prompt);
      for (const part of result.response.candidates[0].content.parts) {
        if (part.inlineData) {
          const imageData = part.inlineData.data;
          return {
            content: [{
              type: "image",
              data: imageData,
              mimeType: `image/${outputFormat}`
            }]
          };
        }
      }
    } catch (error) {
      console.error("Image generation error:", error);
      return {
        content: [{
          type: "text",
          text: `Error generating image: ${error.message}`
        }]
      };
    }
  },

• server.js:20-24 (schema)

  Zod schema defining the input parameters for the generateImage tool: required 'prompt' string, optional 'aspectRatio' and 'outputFormat' strings.

  {
    prompt: z.string(),
    aspectRatio: z.string().optional(),
    outputFormat: z.string().optional()
  },

• server.js:18-70 (registration)

  The MCP server.tool() call that registers the 'generateImage' tool, specifying name, input schema, handler function, and tool metadata including parameter descriptions.

  server.tool(
    "generateImage",
    {
      prompt: z.string(),
      aspectRatio: z.string().optional(),
      outputFormat: z.string().optional()
    },
    async (params) => {
      const prompt = params.prompt || "rendered image of fly pig";
      const outputFormat = params.outputFormat || "png";
  
      try {
        // Initialize gemini-2.0-flash-exp-image-generation model
        const model = genAI.getGenerativeModel({
          model: "gemini-2.0-flash-exp-image-generation",
          generationConfig: {
              responseModalities: ['Text', 'Image'],
          },
        });
  
        // Generate the image
        const result = await model.generateContent(prompt);
        for (const part of result.response.candidates[0].content.parts) {
          if (part.inlineData) {
            const imageData = part.inlineData.data;
            return {
              content: [{
                type: "image",
                data: imageData,
                mimeType: `image/${outputFormat}`
              }]
            };
          }
        }
      } catch (error) {
        console.error("Image generation error:", error);
        return {
          content: [{
            type: "text",
            text: `Error generating image: ${error.message}`
          }]
        };
      }
    },
    {
      description: "Generate an image using Gemini API",
      parameters: {
        prompt: { type: "string", description: "The text description of the image to generate" },
        aspectRatio: { type: "string", description: "Aspect ratio of the image (e.g., '1:1', '16:9')", optional: true },
        outputFormat: { type: "string", description: "Output image format ('png' or 'jpeg')", optional: true }
      }
    }
  );