Pollinations Think MCP Server

/** * Pollinations Image Service * * Functions for interacting with the Pollinations Image API */ /** * Generates an image URL from a text prompt using the Pollinations Image API * * @param {string} prompt - The text description of the image to generate * @param {string} [model='flux'] - Model name to use for generation * @param {number} [seed] - Seed for reproducible results (defaults to random if not specified) * @param {number} [width=1024] - Width of the generated image * @param {number} [height=1024] - Height of the generated image * @param {boolean} [enhance=true] - Whether to enhance the prompt using an LLM before generating * @param {boolean} [safe=false] - Whether to apply content filtering * @returns {Object} - Object containing the image URL and metadata * @note Always includes nologo=true and private=true parameters */ export async function generateImageUrl(prompt, model = 'flux', seed = Math.floor(Math.random() * 1000000), width = 1024, height = 1024, enhance = true, safe = false) { if (!prompt || typeof prompt !== 'string') { throw new Error('Prompt is required and must be a string'); } // Parameters are now directly passed as function arguments // Build the query parameters const queryParams = new URLSearchParams(); // Always include model (with default 'flux') queryParams.append('model', model); // Add other parameters if (seed !== undefined) queryParams.append('seed', seed); if (width) queryParams.append('width', width); if (height) 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}`; // Return the URL directly, keeping it simple return { imageUrl: url, prompt, width, height, model, seed, enhance, private: true, nologo: true, safe }; } /** * Generates an image from a text prompt and returns the image data as base64 * Saves the image to a file by default * * @param {string} prompt - The text description of the image to generate * @param {string} [model='flux'] - Model name to use for generation * @param {number} [seed] - Seed for reproducible results (defaults to random if not specified) * @param {number} [width=1024] - Width of the generated image * @param {number} [height=1024] - Height of the generated image * @param {boolean} [enhance=true] - Whether to enhance the prompt using an LLM before generating * @param {boolean} [safe=false] - Whether to apply content filtering * @param {string} [outputPath='./mcpollinations-output'] - Directory path where to save the image * @param {string} [fileName] - Name of the file to save (without extension) * @param {string} [format='png'] - Image format to save as (png, jpeg, jpg, webp) * @returns {Promise<Object>} - Object containing the base64 image data, mime type, metadata, and file path if saved * @note Always includes nologo=true and private=true parameters */ export async function generateImage(prompt, model = 'flux', seed = Math.floor(Math.random() * 1000000), width = 1024, height = 1024, enhance = true, safe = false, outputPath = './mcpollinations-output', fileName = '', format = 'png') { if (!prompt || typeof prompt !== 'string') { throw new Error('Prompt is required and must be a string'); } // First, generate the image URL const urlResult = await generateImageUrl(prompt, model, seed, width, height, enhance, safe); try { // Fetch the image from the URL const response = await fetch(urlResult.imageUrl); if (!response.ok) { throw new Error(`Failed to generate image: ${response.statusText}`); } // Get the image data as an ArrayBuffer const imageBuffer = await response.arrayBuffer(); // Convert the ArrayBuffer to a base64 string const base64Data = Buffer.from(imageBuffer).toString('base64'); // Determine the mime type from the response headers or default to image/jpeg const contentType = response.headers.get('content-type') || 'image/jpeg'; // Prepare the result object const result = { data: base64Data, mimeType: contentType, metadata: { prompt: urlResult.prompt, width: urlResult.width, height: urlResult.height, model: urlResult.model, seed: urlResult.seed, enhance: urlResult.enhance, private: urlResult.private, nologo: urlResult.nologo, safe: urlResult.safe } }; // Always save the image to a file // Import required modules const fs = await import('fs'); const path = await import('path'); // Create the output directory if it doesn't exist if (!fs.existsSync(outputPath)) { fs.mkdirSync(outputPath, { recursive: true }); } // Validate the file format const validFormats = ['png', 'jpeg', 'jpg', 'webp']; if (!validFormats.includes(format)) { console.warn(`Invalid format '${format}', defaulting to 'png'`); } const extension = validFormats.includes(format) ? format : 'png'; // Generate a file name if not provided or ensure it's unique let baseFileName = fileName; if (!baseFileName) { // Create a safe filename from the prompt (first 20 chars, alphanumeric only) const safePrompt = prompt.slice(0, 20).replace(/[^a-z0-9]/gi, '_').toLowerCase(); const timestamp = Date.now(); // Add a random component to ensure uniqueness const randomSuffix = Math.floor(Math.random() * 10000).toString().padStart(4, '0'); baseFileName = `${safePrompt}_${timestamp}_${randomSuffix}`; } // Ensure the filename is unique to prevent overwriting let fileNameWithSuffix = baseFileName; let filePath = path.join(outputPath, `${fileNameWithSuffix}.${extension}`); let counter = 1; // If the file already exists, add a numeric suffix while (fs.existsSync(filePath)) { fileNameWithSuffix = `${baseFileName}_${counter}`; filePath = path.join(outputPath, `${fileNameWithSuffix}.${extension}`); counter++; } // Save the image to the file fs.writeFileSync(filePath, Buffer.from(base64Data, 'base64')); // Add the file path to the result result.filePath = filePath; return result; } catch (error) { console.error('Error generating image:', error); throw error; } } /** * List available image generation models from Pollinations API * * @returns {Promise<Object>} - Object containing the list of available image models */ export async function listImageModels() { try { const response = await fetch('https://image.pollinations.ai/models'); if (!response.ok) { throw new Error(`Failed to list models: ${response.statusText}`); } return await response.json(); } catch (error) { console.error('Error listing image models:', error); throw error; } }