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editImage

Edit an existing image by providing a text description and image URL. Modify elements like adding or removing objects, or changing backgrounds.

Instructions

Edit or modify an existing image based on a text prompt. User-configured settings in MCP config will be used as defaults unless specifically overridden.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesThe text description of how to edit the image (e.g., "remove the cat and add a dog", "change background to mountains")
imageUrlYesPublic HTTP(S) URL(s) of the input image(s) to edit. Accepts a string or an array for multiple references (first is most important). Local file paths, file uploads, or base64/data URLs are not supported.
modelNoModel name to use for editing (default: user config or "kontext"). Available: "kontext", "nanobanana", "seedream"
seedNoSeed for reproducible results (default: random)
widthNoWidth of the generated image (default: 1024)
heightNoHeight of the generated image (default: 1024)
enhanceNoWhether to enhance the prompt using an LLM before generating (default: true)
safeNoWhether to apply content filtering (default: false)
outputPathNoDirectory path where to save the image (default: user config or "./mcpollinations-output")
fileNameNoName of the file to save (without extension, default: generated from prompt)
formatNoImage format to save as (png, jpeg, jpg, webp - default: png)

Implementation Reference

  • The main handler function for the editImage tool. Takes a prompt and image URL(s), calls the Pollinations Image API, returns base64 image data, and saves the image to disk.
    export async function editImage(prompt, imageUrl, model = 'kontext', seed = Math.floor(Math.random() * 1000000), width = 1024, height = 1024, enhance = true, safe = false, outputPath = './mcpollinations-output', fileName = '', format = 'png', authConfig = null) {
      if (!prompt || typeof prompt !== 'string') {
        throw new Error('Prompt is required and must be a string');
      }
    
      if (!imageUrl || (typeof imageUrl !== 'string' && !Array.isArray(imageUrl))) {
        throw new Error('Image URL(s) are required and must be a string or array of strings');
      }
    
      // Support multi-reference images. Prefer repeating the `image` param per URL
      // to avoid comma-encoding ambiguities.
      const imageList = Array.isArray(imageUrl)
        ? imageUrl.filter(Boolean)
        : (typeof imageUrl === 'string' && imageUrl.includes(','))
          ? imageUrl.split(',').map(s => s.trim()).filter(Boolean)
          : [imageUrl];
    
      // Build the query parameters
      const queryParams = new URLSearchParams();
      queryParams.append('model', model);
      for (const u of imageList) {
        queryParams.append('image', u);
      }
      if (seed !== undefined) queryParams.append('seed', seed);
      if (width !== 1024) queryParams.append('width', width);
      if (height !== 1024) queryParams.append('height', height);
    
      // Add enhance parameter if true
      if (enhance) queryParams.append('enhance', 'true');
    
      // Add parameters
      queryParams.append('nologo', 'true'); // Always set nologo to true
      queryParams.append('private', 'true'); // Always set private to true)
      queryParams.append('safe', safe.toString()); // Use the customizable safe parameter
    
      // Construct the URL
      const encodedPrompt = encodeURIComponent(prompt);
      const baseUrl = 'https://image.pollinations.ai';
      let url = `${baseUrl}/prompt/${encodedPrompt}`;
    
      // Add query parameters
      const queryString = queryParams.toString();
      url += `?${queryString}`;
    
      try {
        // Prepare fetch options with optional auth headers
        const fetchOptions = {};
        if (authConfig) {
          fetchOptions.headers = {};
          if (authConfig.token) {
            fetchOptions.headers['Authorization'] = `Bearer ${authConfig.token}`;
          }
          if (authConfig.referrer) {
            fetchOptions.headers['Referer'] = authConfig.referrer;
          }
        }
    
        // Fetch the image from the URL
        const response = await fetch(url, fetchOptions);
    
        if (!response.ok) {
          throw new Error(`Failed to edit image: ${response.statusText}`);
        }
    
        // Get the image data as an ArrayBuffer
        const imageBuffer = await response.arrayBuffer();
    
        // Convert the ArrayBuffer to a base64 string
        const base64Data = Buffer.from(imageBuffer).toString('base64');
    
        // Determine the mime type from the response headers or default to image/jpeg
        const contentType = response.headers.get('content-type') || 'image/jpeg';
    
        // Prepare the result object
        const result = {
          data: base64Data,
          mimeType: contentType,
          metadata: {
            prompt,
            inputImageUrl: imageUrl,
            width,
            height,
            model,
            seed,
            enhance,
            private: true,
            nologo: true,
            safe
          }
        };
    
        // Always save the image to a file
        // Import required modules
        const fs = await import('fs');
        const path = await import('path');
    
        // Create the output directory if it doesn't exist
        if (!fs.existsSync(outputPath)) {
          fs.mkdirSync(outputPath, { recursive: true });
        }
    
        // Generate a filename if not provided
        let finalFileName = fileName;
        if (!finalFileName) {
          // Create a filename from the prompt (first 20 characters) and timestamp
          const sanitizedPrompt = prompt.replace(/[^a-zA-Z0-9]/g, '_').substring(0, 20);
          const timestamp = Date.now();
          const randomSuffix = Math.floor(Math.random() * 1000);
          finalFileName = `edited_${sanitizedPrompt}_${timestamp}_${randomSuffix}`;
        }
    
        // Ensure the filename has the correct extension
        const extension = format.toLowerCase();
        if (!finalFileName.endsWith(`.${extension}`)) {
          finalFileName += `.${extension}`;
        }
    
        // Check if file already exists and add a number suffix if needed
        let finalFilePath = path.join(outputPath, finalFileName);
        let counter = 1;
        while (fs.existsSync(finalFilePath)) {
          const nameWithoutExt = finalFileName.replace(`.${extension}`, '');
          const numberedFileName = `${nameWithoutExt}_${counter}.${extension}`;
          finalFilePath = path.join(outputPath, numberedFileName);
          counter++;
        }
    
        // Write the image data to the file
        fs.writeFileSync(finalFilePath, Buffer.from(base64Data, 'base64'));
    
        // Add the file path to the result
        result.filePath = finalFilePath;
    
        return result;
    
      } catch (error) {
        log('Error editing image:', error);
        throw error;
      }
    }
  • Schema definition for the editImage tool, defining input properties (prompt, imageUrl, model, seed, width, height, enhance, safe, outputPath, fileName, format) and validation rules.
     * Schema for the editImage tool
     */
    export const editImageSchema = {
      name: 'editImage',
      description: 'Edit or modify an existing image based on a text prompt. User-configured settings in MCP config will be used as defaults unless specifically overridden.',
      inputSchema: {
        type: 'object',
        properties: {
          prompt: {
            type: 'string',
            description: 'The text description of how to edit the image (e.g., "remove the cat and add a dog", "change background to mountains")'
          },
          imageUrl: {
            oneOf: [
              { type: 'string' },
              { type: 'array', items: { type: 'string' } }
            ],
            description: 'Public HTTP(S) URL(s) of the input image(s) to edit. Accepts a string or an array for multiple references (first is most important). Local file paths, file uploads, or base64/data URLs are not supported.'
          },
          model: {
            type: 'string',
            description: 'Model name to use for editing (default: user config or "kontext"). Available: "kontext", "nanobanana", "seedream"'
          },
          seed: {
            type: 'number',
            description: 'Seed for reproducible results (default: random)'
          },
          width: {
            type: 'number',
            description: 'Width of the generated image (default: 1024)'
          },
          height: {
            type: 'number',
            description: 'Height of the generated image (default: 1024)'
          },
          enhance: {
            type: 'boolean',
            description: 'Whether to enhance the prompt using an LLM before generating (default: true)'
          },
          safe: {
            type: 'boolean',
            description: 'Whether to apply content filtering (default: false)'
          },
          outputPath: {
            type: 'string',
            description: 'Directory path where to save the image (default: user config or "./mcpollinations-output")'
          },
          fileName: {
            type: 'string',
            description: 'Name of the file to save (without extension, default: generated from prompt)'
          },
          format: {
            type: 'string',
            description: 'Image format to save as (png, jpeg, jpg, webp - default: png)'
          }
        },
        required: ['prompt', 'imageUrl']
      }
    };
  • MCP server registration of the editImage tool handler. Extracts args, calls the editImage function, and formats the response with image data and metadata.
    } else if (name === 'editImage') {
      try {
        const { prompt, imageUrl, model = 'kontext', seed, width = defaultConfig.image.width, height = defaultConfig.image.height, enhance = defaultConfig.image.enhance, safe = defaultConfig.image.safe, outputPath = defaultConfig.resources.output_dir, fileName = '', format = 'png' } = args;
        const result = await editImage(prompt, imageUrl, model, seed, width, height, enhance, safe, outputPath, fileName, format, finalAuthConfig);
    
        // Prepare the response content
        const content = [
          {
            type: 'image',
            data: result.data,
            mimeType: result.mimeType
          }
        ];
    
        // Prepare the response text
        let responseText = `Edited image from prompt: "${prompt}"\nInput image: ${imageUrl}\n\nImage metadata: ${JSON.stringify(result.metadata, null, 2)}`;
    
        // Add file path information if the image was saved to a file
        if (result.filePath) {
          responseText += `\n\nImage saved to: ${result.filePath}`;
        }
    
        content.push({
          type: 'text',
          text: responseText
        });
    
        return { content };
      } catch (error) {
        return {
          content: [
            { type: 'text', text: `Error editing image: ${error.message}` }
          ],
          isError: true
        };
      }
  • src/schemas.js:32-44 (registration)
    Central registration of all tool schemas, including editImageSchema in the getAllToolSchemas() array used by the MCP server's ListToolsRequestSchema handler.
    export function getAllToolSchemas() {
      return [
        generateImageUrlSchema,
        generateImageSchema,
        editImageSchema,
        generateImageFromReferenceSchema,
        listImageModelsSchema,
        respondAudioSchema,
        listAudioVoicesSchema,
        respondTextSchema,
        listTextModelsSchema
      ];
    }
  • Re-exports the editImage function from imageService.js as part of the public API of the src library.
    import { generateImageUrl, generateImage, editImage, generateImageFromReference, listImageModels } from './services/imageService.js';
    import { respondAudio, listAudioVoices } from './services/audioService.js';
    import { respondText, listTextModels } from './services/textService.js';
    
    
    // Export all service functions
    export {
      // Image services
      generateImageUrl,
      generateImage,
      editImage,
      generateImageFromReference,
      listImageModels,
    
      // Audio services
      respondAudio,
      listAudioVoices,
    
      // Text services
      respondText,
      listTextModels,
    };
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must disclose behavioral traits. It does not mention whether editing is non-destructive, required permissions, or side effects like overwriting files.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no wasted words. The first sentence defines purpose, the second adds context about defaults.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having 11 parameters and no output schema, the description does not explain what the tool returns (e.g., URL, file path, success message). Only mentions saving to outputPath.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the description adds no additional meaning beyond what is already in the input schema. Baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool edits/modifies an existing image using a text prompt, distinguishing it from generation tools like generateImage that create new images.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Mentions user-configured defaults can be overridden, but provides no explicit guidance on when to use this tool versus siblings (e.g., generateImage) or any prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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