Initial commit: MCPollinations MCP Server

This initial commit includes:
- Complete MCP server implementation for Pollinations APIs
- Tools for image, text, and audio generation
- Configuration generator for easy setup
- Comprehensive documentation
- MIT license

The server provides 7 tools:
- generateImageUrl & generateImage
- respondText & listTextModels
- respondAudio & listAudioVoices
- listImageModels

All tools support customizable parameters and follow MCP protocol standards.

.gitignore

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+# Dependency directories
+node_modules/
+jspm_packages/
+
+# Output directories
+dist/
+build/
+out/
+
+# Generated image directories
+mcpollinations-output/
+mcpollinations-temp/
+
+# Development files
+OVERVIEW.md 
+test-image-save.js
+test-list-tools.js
+
+# Environment variables
+.env
+.env.local
+.env.development.local
+.env.test.local
+.env.production.local
+
+# Debug logs
+logs
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+lerna-debug.log*
+.pnpm-debug.log*
+
+# Coverage directories
+coverage/
+.nyc_output/
+
+# Cache directories
+.npm/
+.eslintcache
+.stylelintcache
+.rpt2_cache/
+.rts2_cache_cjs/
+.rts2_cache_es/
+.rts2_cache_umd/
+
+# Runtime data
+pids
+*.pid
+*.seed
+*.pid.lock
+
+# TypeScript cache
+*.tsbuildinfo
+
+# Optional npm cache directory
+.npm
+
+# Optional eslint cache
+.eslintcache
+
+# dotenv environment variable files
+.env
+.env.development.local
+.env.test.local
+.env.production.local
+.env.local
+
+# parcel-bundler cache
+.cache
+.parcel-cache
+
+# Next.js build output
+.next
+out
+
+# Nuxt.js build / generate output
+.nuxt
+dist
+
+# Gatsby files
+.cache/
+public
+
+# vuepress build output
+.vuepress/dist
+
+# vuepress v2.x temp and cache directory
+.temp
+.cache
+
+# Docusaurus cache and generated files
+.docusaurus
+
+# Serverless directories
+.serverless/
+
+# FuseBox cache
+.fusebox/
+
+# DynamoDB Local files
+.dynamodb/
+
+# TernJS port file
+.tern-port
+
+# Stores VSCode versions used for testing VSCode extensions
+.vscode-test
+
+# yarn v2
+.yarn/cache
+.yarn/unplugged
+.yarn/build-state.yml
+.yarn/install-state.gz
+.pnp.*
+
+# macOS
+.DS_Store
+.AppleDouble
+.LSOverride
+Icon
+._*
+.DocumentRevisions-V100
+.fseventsd
+.Spotlight-V100
+.TemporaryItems
+.Trashes
+.VolumeIcon.icns
+.com.apple.timemachine.donotpresent
+
+# Windows
+Thumbs.db
+Thumbs.db:encryptable
+ehthumbs.db
+ehthumbs_vista.db
+*.stackdump
+[Dd]esktop.ini
+$RECYCLE.BIN/
+*.cab
+*.msi
+*.msix
+*.msm
+*.msp
+*.lnk
+
+# Linux
+*~
+.fuse_hidden*
+.directory
+.Trash-*
+.nfs*
+
+# IDE - VSCode
+.vscode/*
+!.vscode/settings.json
+!.vscode/tasks.json
+!.vscode/launch.json
+!.vscode/extensions.json
+*.code-workspace
+.history/
+
+# IDE - JetBrains (WebStorm, IntelliJ, etc)
+.idea/
+*.iml
+*.iws
+*.ipr
+.idea_modules/
+out/
+
+# IDE - Eclipse
+.project
+.classpath
+.settings/
+.metadata
+bin/
+tmp/
+*.tmp
+*.bak
+*.swp
+*~.nib
+local.properties
+.loadpath
+.recommenders
+
+# Generated files
+*.generated.*

.npmignore

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+# Test files and outputs
+test-output/
+*-output/
+*.test.js
+test-*.js
+
+# Development files
+.env
+.env.*
+node_modules/
+.git/
+.github/
+.gitignore
+.vscode/
+.roo/
+.roorules
+
+# Logs
+*.log
+npm-debug.log*

CHANGELOG.md

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+ 📜 Changelog
+
+All notable changes to the MCPollinations will be documented in this file.
+
+The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
+and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
+
+## [1.0.7] - `2025-04-08`
+
+### Added
+- Project analysis and `OVERVIEW.md` update by Pink Pixel on `2025-04-08`.
+- Added Usage and Key Features sections to OVERVIEW.md.
+- Comprehensive codebase analysis.
+- Added ability to save generated images to a customizable file path as PNG (or other formats).
+- New options for `generateImage` tool: `saveToFile`, `outputPath`, `fileName`, and `format`.
+- Added hardcoded parameter `nologo=true` for all image generation.
+- Added customizable parameter `safe` for content filtering (defaults to false).
+- Set default seed to random for image generation to ensure variety.
+- Added customizable parameter `enhance` for image quality enhancement.
+- Set 'flux' as the default model for image generation.
+- Changed default behavior to save images to file automatically (PNG format).
+- Added comprehensive documentation in README.md about image saving behavior, locations, and accessing base64 data.
+- Implemented unique filename generation to prevent overwriting existing images.
+- Added automatic numeric suffixes for duplicate filenames.
+- Renamed `generateText` tool to `respondText` for clarity and consistency.
+- Removed `sayText` tool as it's not supported by the API.
+- Removed generic `listModels` tool in favor of specific `listImageModels` and `listTextModels` tools for clarity.
+- Ensured `model` parameter is properly documented as customizable for text generation.
+- Improved `listAudioVoices` tool to return the complete list of available voices.
+- Enhanced documentation for the `voice` parameter in `respondAudio` tool.
+- Fixed tool registration to ensure all tools are properly displayed in the MCP protocol.
+- Added test script to verify tool registration.
+- Standardized package name references throughout the codebase.
+- Replaced Claude-specific installation script with a comprehensive MCP configuration generator that supports customizing:
+  - Output and temporary directories (using relative paths for portability)
+  - Default parameters for image, text, and audio generation
+  - Tool restrictions and permissions
+  - Fixed server and package names to ensure compatibility
+  - Removed nologo parameter from configuration as it's hardcoded to true
+  - Added lists of available models for image and text generation to help users make informed choices
+- Changed the command to start the server from "model-context-protocol" to "mcpollinations" for better branding consistency
+- Removed `listPrompts` and `listResources` tools as they're not currently implemented with an API
+- Removed resourceService.js and resourceSchema.js files
+- Updated tool schemas to expose only the parameters we want to customize in the MCP client
+- Added MIT LICENSE file
+- Added comprehensive .gitignore file
+- Updated documentation to reflect the new configuration generator.
+
+## [1.0.6] - `2025-04-01`
+
+### Added
+- Compatibility with Node.js versions 14.0.0 and later.
+- AbortController polyfill for Node.js versions below 16.0.0.
+- Troubleshooting guide in README.
+- Enhanced documentation with system requirements and installation options.
+
+### Fixed
+- "AbortController is not defined" error.
+- Improved error handling and reporting.
+
+## [1.0.5] - `2025-04-01`
+
+### Added
+- Initial public release.

CONTRIBUTING.md

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+# Contributing to MCPollinations ✨
+
+First off, thanks for considering contributing! 🎉 This project is exciting, and contributions help make it even better.
+
+## How Can I Contribute?
+
+*   **Reporting Bugs:** If you find a bug, please open an issue on the GitHub repository. Include detailed steps to reproduce the bug, the expected behavior, and the actual behavior.
+*   **Suggesting Enhancements:** Have an idea for a new feature or an improvement? Open an issue to discuss it.
+*   **Pull Requests:** If you've fixed a bug or implemented a new feature, feel free to submit a pull request!
+
+## Pull Request Process
+
+1.  Ensure any install or build dependencies are removed before the end of the layer when doing a build.
+2.  Update the README.md with details of changes to the interface, this includes new environment variables, exposed ports, useful file locations and container parameters.
+3.  Increase the version numbers in any examples files and the README.md to the new version that this Pull Request would represent. The versioning scheme we use is [SemVer](http://semver.org/).
+4.  You may merge the Pull Request in once you have the sign-off of two other developers, or if you do not have permission to do that, you may request the second reviewer to merge it for you.
+
+We appreciate your contributions! ❤️
+
+*Made with ❤️ by Pink Pixel*

LICENSE

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+MIT License
+
+Copyright (c) 2025 Pink Pixel
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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+# MCPollinations Multimodal MCP Server
+
+A Model Context Protocol (MCP) server that enables AI assistants to generate images, text, and audio through the Pollinations APIs
+
+## Features
+
+- Generate image URLs from text prompts
+- Generate images and return them as base64-encoded data AND save as png, jpeg, jpg, or webp (default: png)
+- Generate text responses from text prompts
+- Generate audio responses from text prompts
+- List available image and text generation models
+- No authentication required
+- Simple and lightweight
+- Compatible with the Model Context Protocol (MCP)
+
+## System Requirements
+
+- **Node.js**: Version 14.0.0 or higher
+  - For best performance, we recommend Node.js 16.0.0 or higher
+  - Node.js versions below 16 use an AbortController polyfill
+
+## Quick Start
+
+The easiest way to use the MCP server:
+
+```bash
+# Run directly with npx (no installation required)
+npx @pinkpixel/mcpollinations
+```
+
+If you prefer to install it globally:
+
+```bash
+# Install globally
+npm install -g @pinkpixel/mcpollinations
+
+# Run the server
+mcpollinations
+# or
+npx @pinkpixel/mcpollinations
+
+```
+
+Or clone the repository:
+
+```bash
+# Clone the git repository
+git clone https://github.com/pinkpixel-dev/mcpollinations.git
+# Run the server
+mcpollinations
+# or
+npx @pinkpixel/mcpollinations
+# or run directly
+node /path/to/MCPollinations/pollinations-mcp-server.js
+
+```
+
+## MCP Integration
+
+To integrate the server with applications that support the Model Context Protocol (MCP):
+
+1. Generate an MCP configuration file:
+
+```bash
+# If installed globally
+npx @pinkpixel/mcpollinations generate-config
+
+# Or run directly
+node /path/to/MCPollinations/generate-mcp-config.js
+```
+
+2. Follow the prompts to customize your configuration or use the defaults.
+   - Set custom output and temporary directories (defaults to relative paths for portability)
+   - Configure default parameters for image generation (with a list of available models, dimensions, etc.)
+   - Configure default parameters for text generation (with a list of available models)
+   - Configure default parameters for audio generation (voice)
+   - Specify which tools should be allowed
+
+3. Copy the generated `mcp.json` file to your application's MCP settings .json file.
+4. Restart your application.
+
+After integration, you can use commands like:
+
+"Generate an image of a sunset over the ocean using MCPollinations"
+
+
+## Troubleshooting
+
+### "AbortController is not defined" Error
+
+If you encounter this error when running the MCP server:
+
+```
+ReferenceError: AbortController is not defined
+```
+
+This is usually caused by running on an older version of Node.js (below version 16.0.0). Try one of these solutions:
+
+1. **Update Node.js** (recommended):
+   - Update to Node.js 16.0.0 or newer
+
+2. **Use Global Installation**
+   - Update to the latest version of the package:
+   ```bash
+   npm install -g @pinkpixel/mcpollinations
+   # Run with npx
+   npx @pinkpixel/mcpollinations
+   ```
+
+3. **Install AbortController manually**:
+   - If for some reason the polyfill doesn't work:
+   ```bash
+   npm install node-abort-controller
+   ```
+
+### Check Your Node.js Version
+
+To check your current Node.js version:
+
+```bash
+node --version
+```
+
+If it shows a version lower than 16.0.0, consider upgrading for best compatibility.
+
+## Available Tools
+
+The MCP server provides the following tools:
+
+1. `generateImageUrl` - Generates an image URL from a text prompt
+2. `generateImage` - Generates an image, returns it as base64-encoded data, and saves it to a file by default (PNG format)
+3. `respondAudio` - Generates an audio response to a text prompt (customizable voice parameter)
+4. `respondText` - Responds with text to a prompt using text models (customizable model parameter)
+5. `listImageModels` - Lists available models for image generation
+6. `listTextModels` - Lists available models for text generation
+7. `listAudioVoices` - Lists all available voices for audio generation
+
+## Image Generation Details
+
+### Default Behavior
+
+When using the `generateImage` tool:
+
+- Images are saved to disk by default as PNG files
+- The default save location is the current working directory where the MCP server is running
+- The 'flux' model is used by default
+- A random seed is generated by default for each image (ensuring variety)
+- Base64-encoded image data is always returned, regardless of whether the image is saved to a file
+
+### Customizing Image Generation
+
+```javascript
+// Example options for generateImage
+const options = {
+  // Model selection (defaults to 'flux')
+  model: "flux",
+
+  // Image dimensions
+  width: 1024,
+  height: 1024,
+
+  // Generation options
+  seed: 12345,  // Specific seed for reproducibility (defaults to random)
+  enhance: true,  // Enhance the prompt using an LLM before generating (defaults to true)
+  safe: false,  // Content filtering (defaults to false)
+
+  // File saving options
+  saveToFile: true,  // Set to false to skip saving to disk
+  outputPath: "/path/to/save/directory",  // Custom save location
+  fileName: "my_custom_name",  // Without extension
+  format: "png"  // png, jpeg, jpg, or webp
+};
+```
+
+### Where Images Are Saved
+
+When using Claude or another application with the MCP server:
+
+1. **Images are saved in the current working directory of where the MCP server is running**, not where Claude or the client application is installed.
+
+2. If you start the MCP server manually from a specific directory, images will be saved there by default.
+
+3. If Claude Desktop launches the MCP server automatically, images will be saved in Claude Desktop's working directory (typically in an application data folder).
+
+### Finding Your Generated Images
+
+- The response from Claude after generating an image includes the full file path where the image was saved
+- You can specify a familiar location using the `outputPath` parameter
+- Best practice: Ask Claude to save images to an easily accessible folder like your Pictures or Downloads directory
+
+### Unique Filenames
+
+The MCP server ensures that generated images always have unique filenames and will never overwrite existing files:
+
+1. **Default filenames** include:
+   - A sanitized version of the prompt (first 20 characters)
+   - A timestamp
+   - A random suffix
+
+2. **Custom filenames** are also protected:
+   - If you specify a filename and a file with that name already exists, a numeric suffix will be added automatically
+   - For example: `sunset.png`, `sunset_1.png`, `sunset_2.png`, etc.
+
+This means you can safely generate multiple images with the same prompt or filename without worrying about overwriting previous images.
+
+### Accessing Base64 Data
+
+Even when saving to a file, the base64-encoded image data is always returned and can be used for:
+
+- Embedding in web pages (`<img src="data:image/png;base64,..." />`)
+- Passing to other services or APIs
+- Processing in memory without filesystem operations
+- Displaying in applications that support data URIs
+
+## For Developers
+
+If you want to use the package in your own projects:
+
+```bash
+# Install as a dependency
+npm install @pinkpixel/mcpollinations
+
+# Import in your code
+import { generateImageUrl, generateImage, repsondText, respondAudio, listTextModels, listImageModels, listAudioVoices } from '@pinkpixel/mcpollinations';
+```

example-mcp.json

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+{
+  "mcpollinations": {
+    "command": "npx",
+    "args": [
+      "-y",
+      "@pinkpixel/mcpollinations"
+    ],
+    "resources": {
+      "output_dir": "./mcpollinations-output"
+    },
+    "default_params": {
+      "image": {
+        "model": "flux",
+        "width": 1024,
+        "height": 1024,
+        "safe": false,
+        "enhance": true
+      },
+      "text": {
+        "model": "openai"
+      },
+      "audio": {
+        "voice": "alloy"
+      }
+    },
+    "disabled": false,
+    "alwaysAllow": [
+      "generateImageUrl",
+      "generateImage",
+      "listImageModels",
+      "respondAudio",
+      "listAudioVoices",
+      "respondText",
+      "listTextModels"
+    ]
+  }
+}

generate-mcp-config.js

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+#!/usr/bin/env node
+import fs from 'fs';
+import readline from 'readline';
+
+// Create readline interface for user input
+const rl = readline.createInterface({
+  input: process.stdin,
+  output: process.stdout
+});
+
+// Default configuration template
+const defaultConfig = {
+  "mcpollinations": {
+    "command": "npx",
+    "args": [
+      "-y",
+      "@pinkpixel/mcpollinations"
+    ],
+    "resources": {
+      "output_dir": "./mcpollinations-output",
+    },
+    "default_params": {
+      "image": {
+        "model": "flux",
+        "width": 1024,
+        "height": 1024,
+        "safe": false,
+        "enhance": true
+      },
+      "text": {
+        "model": "openai"
+      },
+      "audio": {
+        "voice": "alloy"
+      }
+    },
+    "disabled": false,
+    "alwaysAllow": [
+      "generateImageUrl",
+      "generateImage",
+      "listImageModels",
+      "respondAudio",
+      "listAudioVoices",
+      "respondText",
+      "listTextModels"
+    ]
+  }
+};
+
+// Function to prompt user for input
+function prompt(question) {
+  return new Promise((resolve) => {
+    rl.question(question, (answer) => {
+      resolve(answer);
+    });
+  });
+}
+
+// Function to prompt user for yes/no input
+async function promptYesNo(question, defaultYes = true) {
+  const defaultOption = defaultYes ? 'Y/n' : 'y/N';
+  const response = await prompt(`${question} (${defaultOption}): `);
+  if (response === '') return defaultYes;
+  return response.toLowerCase() === 'y';
+}
+
+// Function to generate the MCP configuration
+async function generateMcpConfig() {
+  console.log('MCPollinations MCP Configuration Generator');
+  console.log('=========================================');
+  console.log('This tool will help you create an MCP configuration file for the MCPollinations server.');
+  console.log('You can use this configuration with any application that supports the Model Context Protocol.');
+  console.log('');
+
+  // Ask for configuration options
+  const useDefaults = await promptYesNo('Use default configuration?');
+
+  let config = JSON.parse(JSON.stringify(defaultConfig)); // Deep copy
+
+  if (!useDefaults) {
+    console.log('\nCustomizing configuration:');
+
+    // The server name and package name are fixed to ensure compatibility
+    const configKey = 'mcpollinations';
+
+    // Resources customization
+    console.log('\nResource Directories:');
+    console.log('Note: Using relative path (starting with "./") is recommended for portability.');
+    console.log('These directories will be created automatically if they don\'t exist.');
+
+    const outputDir = await prompt(`Output directory for saved files (default: "${config[configKey].resources.output_dir}"): `);
+    if (outputDir) {
+      config[configKey].resources.output_dir = outputDir;
+    }
+
+    // Default parameters customization
+    console.log('\nDefault Parameters:');
+
+    // Image parameters
+    console.log('\nImage Generation Parameters:');
+    const customizeImage = await promptYesNo('Customize image generation parameters?', false);
+
+    if (customizeImage) {
+      console.log('Available image models: "flux", "turbo" (sdxl)');
+      const imageModel = await prompt('Default image model (default: "flux"): ');
+      if (imageModel) config[configKey].default_params.image.model = imageModel;
+
+      const imageWidth = await prompt('Default image width (default: 1024): ');
+      if (imageWidth) config[configKey].default_params.image.width = parseInt(imageWidth);
+
+      const imageHeight = await prompt('Default image height (default: 1024): ');
+      if (imageHeight) config[configKey].default_params.image.height = parseInt(imageHeight);
+
+      const imageSafe = await promptYesNo('Enable safe mode for images? (default: false)', false);
+      config[configKey].default_params.image.safe = imageSafe;
+
+      const imageEnhance = await promptYesNo('Enable prompt enhancement using LLM before image generation?', true);
+      config[configKey].default_params.image.enhance = imageEnhance;
+    }
+
+    // Text parameters
+    console.log('\nText Generation Parameters:');
+    const customizeText = await promptYesNo('Customize text generation parameters?', false);
+
+    if (customizeText) {
+      console.log('Available text models: "openai", "anthropic", "mistral", "llama", "gemini" - use listTextModels to see all models');
+      const textModel = await prompt('Default text model (default: "openai"): ');
+      if (textModel) config[configKey].default_params.text.model = textModel;
+    }
+
+    // Audio parameters
+    console.log('\nAudio Generation Parameters:');
+    const customizeAudio = await promptYesNo('Customize audio generation parameters?', false);
+
+    if (customizeAudio) {
+      console.log('Available voices: "alloy", "echo", "fable", "onyx", "nova", "shimmer", "coral", "verse", "ballad", "ash", "sage", "amuch", "dan"');
+      const audioVoice = await prompt('Default voice (default: "alloy"): ');
+      if (audioVoice) config[configKey].default_params.audio.voice = audioVoice;
+    }
+
+    // Tool restrictions
+    console.log('\nTool Restrictions:');
+    const disableServer = await promptYesNo('Disable the server by default?', false);
+    config[configKey].disabled = disableServer;
+
+    const customizeAllowedTools = await promptYesNo('Customize allowed tools?', false);
+    if (customizeAllowedTools) {
+      console.log('\nAvailable tools:');
+      const allTools = [
+        'generateImageUrl',
+        'generateImage',
+        'listImageModels',
+        'respondAudio',
+        'listAudioVoices',
+        'respondText',
+        'listTextModels'
+      ];
+
+      allTools.forEach((tool, index) => {
+        console.log(`${index + 1}. ${tool}`);
+      });
+
+      const selectedTools = await prompt('Enter tool numbers to allow (comma-separated, e.g., "1,2,3") or "all" for all tools: ');
+
+      if (selectedTools.toLowerCase() === 'all') {
+        config[configKey].alwaysAllow = [...allTools];
+      } else {
+        const toolIndices = selectedTools.split(',').map(num => parseInt(num.trim()) - 1);
+        config[configKey].alwaysAllow = toolIndices
+          .filter(index => index >= 0 && index < allTools.length)
+          .map(index => allTools[index]);
+      }
+    }
+  }
+
+  // Ask for output options
+  console.log('\nOutput options:');
+  const outputPath = await prompt('Output file path (default: "./mcp.json"): ');
+  const filePath = outputPath || './mcp.json';
+
+  // Write the configuration to a file
+  try {
+    fs.writeFileSync(filePath, JSON.stringify(config, null, 2));
+    console.log(`\nMCP configuration saved to: ${filePath}`);
+    console.log('\nYou can now use this configuration with any application that supports the Model Context Protocol.');
+    console.log('For example, you can add this configuration to your application\'s MCP configuration directory.');
+
+    // Display the configuration
+    console.log('\nGenerated configuration:');
+    console.log(JSON.stringify(config, null, 2));
+  } catch (error) {
+    console.error(`Error saving configuration: ${error.message}`);
+  }
+
+  rl.close();
+}
+
+// Run the generator
+generateMcpConfig().catch(console.error);

package-lock.json

@@ -0,0 +1,1209 @@
+{
+  "name": "@pinkpixel/mcpollinations",
+  "version": "1.0.8",
+  "lockfileVersion": 3,
+  "requires": true,
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+      }
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+      "license": "MIT",
+      "funding": {
+        "url": "https://github.com/sponsors/colinhacks"
+      }
+    },
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+      "license": "ISC",
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+    },
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+}

package.json

@@ -0,0 +1,47 @@
+{
+  "name": "@pinkpixel/mcpollinations",
+  "version": "1.0.8",
+  "description": "Model Context Protocol (MCP) server for the Pollinations APIs with image saving functionality.",
+  "type": "module",
+  "bin": {
+    "mcpollinations": "./pollinations-mcp-server.js"
+  },
+  "files": [
+    "src/**/*",
+    "pollinations-mcp-server.js",
+    "generate-mcp-config.js",
+    "README.md",
+    "LICENSE"
+  ],
+  "scripts": {
+    "test": "node test-mcp-client.js",
+    "test:image-save": "node test-image-save.js",
+    "test:list-tools": "node test-list-tools.js",
+    "start": "node pollinations-mcp-server.js",
+    "generate-config": "node generate-mcp-config.js"
+  },
+  "keywords": [
+    "pollinations",
+    "ai",
+    "image",
+    "generation",
+    "model-context-protocol",
+    "mcp"
+  ],
+  "author": "pinkpixel",
+  "license": "MIT",
+  "dependencies": {
+    "@modelcontextprotocol/sdk": "^1.7.0",
+    "@pinkpixel/mcpollinations": "^1.0.8",
+    "node-abort-controller": "^3.1.1",
+    "node-fetch": "^3.3.2",
+    "play-sound": "^1.1.6"
+  },
+  "repository": {
+    "type": "git",
+    "url": "git+https://github.com/pinkpixel-dev/mcpollinations.git"
+  },
+  "engines": {
+    "node": ">=14.0.0"
+  }
+}

pollinations-api-client.js

@@ -0,0 +1,227 @@
+/**
+ * Pollinations API Client
+ * 
+ * A simple client for the Pollinations APIs that doesn't require Cloudflare Workers
+ */
+
+/**
+ * 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 {Object} options - Additional options for image generation
+ * @param {string} [options.model] - Model name to use for generation
+ * @param {number} [options.seed] - Seed for reproducible results
+ * @param {number} [options.width=1024] - Width of the generated image
+ * @param {number} [options.height=1024] - Height of the generated image
+ * @returns {Object} - Object containing the image URL and metadata
+ */
+export async function generateImageUrl(prompt, options = {}) {
+  if (!prompt || typeof prompt !== 'string') {
+    throw new Error('Prompt is required and must be a string');
+  }
+
+  const { 
+    model, 
+    seed, 
+    width = 1024, 
+    height = 1024,
+  } = options;
+  
+  // Build the query parameters
+  const queryParams = new URLSearchParams();
+  if (model) queryParams.append('model', model);
+  if (seed !== undefined) queryParams.append('seed', seed);
+  if (width) queryParams.append('width', width);
+  if (height) queryParams.append('height', height);
+  
+  // Construct the URL
+  const encodedPrompt = encodeURIComponent(prompt);
+  const baseUrl = 'https://image.pollinations.ai';
+  let url = `${baseUrl}/prompt/${encodedPrompt}`;
+  
+  // Add query parameters if they exist
+  const queryString = queryParams.toString();
+  if (queryString) {
+    url += `?${queryString}`;
+  }
+  
+  // Return the URL directly, keeping it simple
+  return {
+    imageUrl: url,
+    prompt,
+    width,
+    height,
+    model: model || 'flux', // Default model is flux
+    seed
+  };
+}
+
+/**
+ * Generates an image from a text prompt and returns the image data as base64
+ * 
+ * @param {string} prompt - The text description of the image to generate
+ * @param {Object} options - Additional options for image generation
+ * @param {string} [options.model] - Model name to use for generation
+ * @param {number} [options.seed] - Seed for reproducible results
+ * @param {number} [options.width=1024] - Width of the generated image
+ * @param {number} [options.height=1024] - Height of the generated image
+ * @returns {Promise<Object>} - Object containing the base64 image data, mime type, and metadata
+ */
+export async function generateImage(prompt, options = {}) {
+  // First, generate the image URL
+  const result = await generateImageUrl(prompt, options);
+  
+  try {
+    // Fetch the image from the URL
+    const response = await fetch(result.imageUrl);
+    
+    if (!response.ok) {
+      throw new Error(`Failed to fetch image: ${response.statusText}`);
+    }
+    
+    // Get the image data as an ArrayBuffer
+    const imageBuffer = await response.arrayBuffer();
+    
+    // Convert the ArrayBuffer to a base64 string
+    const base64Data = Buffer.from(imageBuffer).toString('base64');
+    
+    // Determine the mime type from the response headers or default to image/png
+    const contentType = response.headers.get('content-type') || 'image/png';
+    
+    return {
+      data: base64Data,
+      mimeType: contentType,
+      metadata: {
+        prompt: result.prompt,
+        width: result.width,
+        height: result.height,
+        model: result.model,
+        seed: result.seed
+      }
+    };
+  } catch (error) {
+    console.error('Error generating image:', error);
+    throw error;
+  }
+}
+
+/**
+ * Generates audio from a text prompt using the Pollinations Text API
+ * 
+ * @param {string} prompt - The text to convert to speech
+ * @param {Object} options - Additional options for audio generation
+ * @param {string} [options.voice="alloy"] - Voice to use for audio generation
+ * @param {number} [options.seed] - Seed for reproducible results
+ * @returns {Promise<Object>} - Object containing the base64 audio data, mime type, and metadata
+ */
+export async function generateAudio(prompt, options = {}) {
+  if (!prompt || typeof prompt !== 'string') {
+    throw new Error('Prompt is required and must be a string');
+  }
+
+  const { 
+    voice = "alloy", 
+    seed,
+  } = options;
+  
+  // Build the query parameters
+  const queryParams = new URLSearchParams();
+  queryParams.append('model', 'openai-audio'); // Required for audio generation
+  queryParams.append('voice', voice);
+  if (seed !== undefined) queryParams.append('seed', seed);
+  
+  // Construct the URL
+  const encodedPrompt = encodeURIComponent(prompt);
+  const baseUrl = 'https://text.pollinations.ai';
+  let url = `${baseUrl}/${encodedPrompt}`;
+  
+  // Add query parameters
+  const queryString = queryParams.toString();
+  url += `?${queryString}`;
+  
+  try {
+    console.error(`Generating audio from URL: ${url}`);
+    
+    // Fetch the audio from the URL
+    const response = await fetch(url);
+    
+    if (!response.ok) {
+      throw new Error(`Failed to generate audio: ${response.statusText}`);
+    }
+    
+    // Get the audio data as an ArrayBuffer
+    const audioBuffer = await response.arrayBuffer();
+    
+    // Convert the ArrayBuffer to a base64 string
+    const base64Data = Buffer.from(audioBuffer).toString('base64');
+    
+    // Determine the mime type from the response headers or default to audio/mpeg
+    const contentType = response.headers.get('content-type') || 'audio/mpeg';
+    
+    return {
+      data: base64Data,
+      mimeType: contentType,
+      metadata: {
+        prompt,
+        voice,
+        model: 'openai-audio',
+        seed
+      }
+    };
+  } catch (error) {
+    console.error('Error generating audio:', error);
+    throw error;
+  }
+}
+
+/**
+ * List available models from Pollinations APIs
+ * 
+ * @param {string} [type="image"] - The type of models to list ("image" or "text")
+ * @returns {Promise<Object>} - Object containing the list of available models
+ */
+export async function listModels(type = "image") {
+  try {
+    const baseUrl = type === "text" ? 
+      'https://text.pollinations.ai' : 
+      'https://image.pollinations.ai';
+    
+    console.error(`Fetching ${type} models from ${baseUrl}/models`);
+    
+    const response = await fetch(`${baseUrl}/models`);
+    
+    if (!response.ok) {
+      throw new Error(`Error fetching models: ${response.statusText}`);
+    }
+    
+    const models = await response.json();
+    return { models };
+  } catch (error) {
+    console.error(`Error in listModels for ${type}:`, error);
+    throw error;
+  }
+}
+
+// If this file is run directly (e.g., with Node.js)
+if (typeof require !== 'undefined' && require.main === module) {
+  async function run() {
+    try {
+      // Example: Generate an image URL
+      const imageUrlResult = await generateImageUrl('A beautiful sunset over the ocean');
+      console.log('Image URL Result:', imageUrlResult);
+      
+      // Example: List available models
+      const modelsResult = await listModels();
+      console.log('Available Models:', modelsResult);
+      
+      // Example: Generate audio
+      console.log('Generating audio...');
+      const audioResult = await generateAudio('Hello world, this is a test of the Pollinations API client.');
+      console.log('Audio generated successfully!');
+    } catch (error) {
+      console.error('Error in example:', error);
+    }
+  }
+  
+  run();
+}

pollinations-mcp-server.js

@@ -0,0 +1,308 @@
+#!/usr/bin/env node
+
+// Check Node.js version and provide polyfill for AbortController if needed
+// This needs to be done before importing any modules that might use AbortController
+const nodeVersion = process.versions.node;
+const majorVersion = parseInt(nodeVersion.split('.')[0], 10);
+
+// Show version info
+console.error(`Running on Node.js version: ${nodeVersion}`);
+
+// Add AbortController polyfill for Node.js versions < 16
+if (majorVersion < 16) {
+  // Check if AbortController is already defined globally
+  if (typeof global.AbortController === 'undefined') {
+    console.error('Adding AbortController polyfill for Node.js < 16');
+    try {
+      // Try to dynamically import a polyfill
+      // First attempt to use node-abort-controller if it's installed
+      try {
+        const { AbortController: AbortControllerPolyfill } = await import('node-abort-controller');
+        global.AbortController = AbortControllerPolyfill;
+      } catch (importError) {
+        // Create a basic implementation if the import fails
+        console.error('Using basic AbortController polyfill');
+
+        class AbortSignal {
+          constructor() {
+            this.aborted = false;
+            this.onabort = null;
+            this._eventListeners = {};
+          }
+
+          addEventListener(type, listener) {
+            if (!this._eventListeners[type]) {
+              this._eventListeners[type] = [];
+            }
+            this._eventListeners[type].push(listener);
+          }
+
+          removeEventListener(type, listener) {
+            if (!this._eventListeners[type]) return;
+            this._eventListeners[type] = this._eventListeners[type].filter(l => l !== listener);
+          }
+
+          dispatchEvent(event) {
+            if (event.type === 'abort' && this.onabort) {
+              this.onabort(event);
+            }
+
+            if (this._eventListeners[event.type]) {
+              this._eventListeners[event.type].forEach(listener => listener(event));
+            }
+          }
+        }
+
+        global.AbortController = class AbortController {
+          constructor() {
+            this.signal = new AbortSignal();
+          }
+
+          abort() {
+            if (this.signal.aborted) return;
+            this.signal.aborted = true;
+            const event = { type: 'abort' };
+            this.signal.dispatchEvent(event);
+          }
+        };
+      }
+    } catch (error) {
+      console.error('Failed to add AbortController polyfill:', error);
+      console.error('This package requires Node.js >= 16. Please upgrade your Node.js version.');
+      process.exit(1);
+    }
+  }
+}
+
+// Now import the MCP SDK and other modules
+import { Server } from '@modelcontextprotocol/sdk/server/index.js';
+import { StdioServerTransport } from '@modelcontextprotocol/sdk/server/stdio.js';
+import {
+  CallToolRequestSchema,
+  ErrorCode,
+  ListToolsRequestSchema,
+  McpError,
+} from '@modelcontextprotocol/sdk/types.js';
+import {
+  generateImageUrl,
+  generateImage,
+  respondAudio,
+  listImageModels,
+  listTextModels,
+  listAudioVoices,
+  respondText,
+
+} from './src/index.js';
+import { getAllToolSchemas } from './src/schemas.js';
+import fs from 'fs';
+import path from 'path';
+import os from 'os';
+import player from 'play-sound';
+
+// Create audio player instance
+const audioPlayer = player({});
+
+// Create the server instance
+const server = new Server(
+  {
+    name: '@pinkpixel/mcpollinations',
+    version: '1.0.8',
+  },
+  {
+    capabilities: {
+      tools: {}
+    }
+  }
+);
+
+// Set up error handling
+server.onerror = (error) => console.error('[MCP Error]', error);
+process.on('SIGINT', async () => {
+  await server.close();
+  process.exit(0);
+});
+
+// Set up tool handlers
+// List available tools
+server.setRequestHandler(ListToolsRequestSchema, async () => ({
+  tools: getAllToolSchemas()
+}));
+
+// Handle tool calls
+server.setRequestHandler(CallToolRequestSchema, async (request) => {
+  const { name, arguments: args } = request.params;
+
+  if (name === 'generateImageUrl') {
+    try {
+      const { prompt, model = 'flux', seed, width = 1024, height = 1024, enhance = true, safe = false } = args;
+      const result = await generateImageUrl(prompt, model, seed, width, height, enhance, safe);
+      return {
+        content: [
+          { type: 'text', text: JSON.stringify(result, null, 2) }
+        ]
+      };
+    } catch (error) {
+      return {
+        content: [
+          { type: 'text', text: `Error generating image URL: ${error.message}` }
+        ],
+        isError: true
+      };
+    }
+  } else if (name === 'generateImage') {
+    try {
+      const { prompt, model = 'flux', seed, width = 1024, height = 1024, enhance = true, safe = false, outputPath = './mcpollinations-output', fileName = '', format = 'png' } = args;
+      const result = await generateImage(prompt, model, seed, width, height, enhance, safe, outputPath, fileName, format);
+
+      // Prepare the response content
+      const content = [
+        {
+          type: 'image',
+          data: result.data,
+          mimeType: result.mimeType
+        }
+      ];
+
+      // Prepare the response text
+      let responseText = `Generated image from prompt: "${prompt}"\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}`;
+      }
+
+      // Add the text content
+      content.push({ type: 'text', text: responseText });
+
+      return { content };
+    } catch (error) {
+      return {
+        content: [
+          { type: 'text', text: `Error generating image: ${error.message}` }
+        ],
+        isError: true
+      };
+    }
+  } else if (name === 'respondAudio') {
+    try {
+      const { prompt, voice, seed, voiceInstructions } = args;
+      const result = await respondAudio(prompt, voice, seed, voiceInstructions);
+
+      // Save audio to a temporary file
+      const tempDir = os.tmpdir();
+      const tempFilePath = path.join(tempDir, `pollinations-audio-${Date.now()}.mp3`);
+
+      // Decode base64 and write to file
+      fs.writeFileSync(tempFilePath, Buffer.from(result.data, 'base64'));
+
+      // Play the audio file
+      audioPlayer.play(tempFilePath, (err) => {
+        if (err) console.error('Error playing audio:', err);
+
+        // Clean up the temporary file after playing
+        try {
+          fs.unlinkSync(tempFilePath);
+        } catch (cleanupErr) {
+          console.error('Error cleaning up temp file:', cleanupErr);
+        }
+      });
+
+      return {
+        content: [
+          {
+            type: 'text',
+            text: `Audio has been played.\n\nAudio metadata: ${JSON.stringify(result.metadata, null, 2)}`
+          }
+        ]
+      };
+    } catch (error) {
+      return {
+        content: [
+          { type: 'text', text: `Error generating audio: ${error.message}` }
+        ],
+        isError: true
+      };
+    }
+  } else if (name === 'listImageModels') {
+    try {
+      const result = await listImageModels();
+      return {
+        content: [
+          { type: 'text', text: JSON.stringify(result, null, 2) }
+        ]
+      };
+    } catch (error) {
+      return {
+        content: [
+          { type: 'text', text: `Error listing image models: ${error.message}` }
+        ],
+        isError: true
+      };
+    }
+  } else if (name === 'listTextModels') {
+    try {
+      const result = await listTextModels();
+      return {
+        content: [
+          { type: 'text', text: JSON.stringify(result, null, 2) }
+        ]
+      };
+    } catch (error) {
+      return {
+        content: [
+          { type: 'text', text: `Error listing text models: ${error.message}` }
+        ],
+        isError: true
+      };
+    }
+  } else if (name === 'listAudioVoices') {
+    try {
+      const result = await listAudioVoices();
+      return {
+        content: [
+          { type: 'text', text: JSON.stringify(result, null, 2) }
+        ]
+      };
+    } catch (error) {
+      return {
+        content: [
+          { type: 'text', text: `Error listing audio voices: ${error.message}` }
+        ],
+        isError: true
+      };
+    }
+  } else if (name === 'respondText') {
+    try {
+      const { prompt, model = "openai", seed } = args;
+      const result = await respondText(prompt, model, seed);
+      return {
+        content: [
+          { type: 'text', text: result }
+        ]
+      };
+    } catch (error) {
+      return {
+        content: [
+          { type: 'text', text: `Error generating text response: ${error.message}` }
+        ],
+        isError: true
+      };
+    }
+
+
+  } else {
+    throw new McpError(
+      ErrorCode.MethodNotFound,
+      `Unknown tool: ${name}`
+    );
+  }
+});
+
+// Run the server
+async function run() {
+  const transport = new StdioServerTransport();
+  await server.connect(transport);
+  console.error('MCPollinations MCP server running on stdio');
+}
+
+run().catch(console.error);

src/index.js

@@ -0,0 +1,57 @@
+/**
+ * Pollinations API Client
+ *
+ * A simple client for the Pollinations APIs that follows the thin proxy design principle
+ */
+
+// Import services
+import { generateImageUrl, generateImage, 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,
+  listImageModels,
+
+  // Audio services
+  respondAudio,
+  listAudioVoices,
+
+  // Text services
+  respondText,
+  listTextModels,
+};
+
+// If this file is run directly (e.g., with Node.js)
+if (typeof require !== 'undefined' && require.main === module) {
+  async function run() {
+    try {
+      console.log('Testing Pollinations API client...');
+
+      // Test image URL generation
+      const imageUrl = await generateImageUrl('A beautiful sunset over the ocean');
+      console.log('Image URL:', imageUrl);
+
+      // Test model listing
+      const imageModels = await listImageModels();
+      console.log('Image models:', imageModels);
+
+      const textModels = await listTextModels();
+      console.log('Text models:', textModels);
+
+      const voices = await listAudioVoices();
+      console.log('Audio voices:', voices);
+
+
+
+    } catch (error) {
+      console.error('Error:', error);
+    }
+  }
+
+  run();
+}

src/schemas.js

@@ -0,0 +1,40 @@
+/**
+ * Central export for all schema definitions
+ */
+
+import { generateImageUrlSchema, generateImageSchema, listImageModelsSchema } from './services/imageSchema.js';
+import { respondAudioSchema, listAudioVoicesSchema } from './services/audioSchema.js';
+import { respondTextSchema, listTextModelsSchema } from './services/textSchema.js';
+
+
+// Re-export all schemas
+export {
+  // Image schemas
+  generateImageUrlSchema,
+  generateImageSchema,
+  listImageModelsSchema,
+
+  // Audio schemas
+  respondAudioSchema,
+  listAudioVoicesSchema,
+
+  // Text schemas
+  respondTextSchema,
+  listTextModelsSchema
+};
+
+/**
+ * Get all tool schemas as an array
+ * @returns {Array} Array of all tool schemas
+ */
+export function getAllToolSchemas() {
+  return [
+    generateImageUrlSchema,
+    generateImageSchema,
+    listImageModelsSchema,
+    respondAudioSchema,
+    listAudioVoicesSchema,
+    respondTextSchema,
+    listTextModelsSchema
+  ];
+}

src/services/audioSchema.js

@@ -0,0 +1,43 @@
+/**
+ * Schema definitions for the Pollinations Audio API
+ */
+
+/**
+ * Schema for the respondAudio tool
+ */
+export const respondAudioSchema = {
+  name: 'respondAudio',
+  description: 'Generate an audio response to a text prompt and play it through the system',
+  inputSchema: {
+    type: 'object',
+    properties: {
+      prompt: {
+        type: 'string',
+        description: 'The text prompt to respond to with audio'
+      },
+      voice: {
+        type: 'string',
+        description: 'Voice to use for audio generation (default: "alloy"). Available options: "alloy", "echo", "fable", "onyx", "nova", "shimmer", "coral", "verse", "ballad", "ash", "sage", "amuch", "dan"'
+      },
+      seed: {
+        type: 'number',
+        description: 'Seed for reproducible results (default: random)'
+      }
+    },
+    required: ['prompt']
+  }
+};
+
+
+
+/**
+ * Schema for the listAudioVoices tool
+ */
+export const listAudioVoicesSchema = {
+  name: 'listAudioVoices',
+  description: 'List all available audio voices for text-to-speech generation',
+  inputSchema: {
+    type: 'object',
+    properties: {}
+  }
+};

src/services/audioService.js

@@ -0,0 +1,103 @@
+/**
+ * Pollinations Audio Service
+ *
+ * Functions for interacting with the Pollinations Audio API
+ */
+
+/**
+ * Generates an audio response to a text prompt using the Pollinations Text API
+ *
+ * @param {string} prompt - The text prompt to respond to with audio
+ * @param {string} [voice="alloy"] - Voice to use for audio generation. Available options: "alloy", "echo", "fable", "onyx", "nova", "shimmer", "coral", "verse", "ballad", "ash", "sage", "amuch", "dan"
+ * @param {number} [seed] - Seed for reproducible results
+ * @param {string} [voiceInstructions] - Additional instructions for voice character/style
+ * @returns {Promise<Object>} - Object containing the base64 audio data, mime type, and metadata
+ */
+export async function respondAudio(prompt, voice = "alloy", seed, voiceInstructions) {
+  if (!prompt || typeof prompt !== 'string') {
+    throw new Error('Prompt is required and must be a string');
+  }
+
+  // Build the query parameters
+  const queryParams = new URLSearchParams();
+  queryParams.append('model', 'openai-audio'); // Required for audio generation
+  queryParams.append('voice', voice);
+  if (seed !== undefined) queryParams.append('seed', seed);
+
+  // Construct the URL
+  let finalPrompt = prompt;
+
+  // Add voice instructions if provided
+  if (voiceInstructions) {
+    finalPrompt = `${voiceInstructions}\n\n${prompt}`;
+  }
+
+  const encodedPrompt = encodeURIComponent(finalPrompt);
+  const baseUrl = 'https://text.pollinations.ai';
+  let url = `${baseUrl}/${encodedPrompt}`;
+
+  // Add query parameters
+  const queryString = queryParams.toString();
+  url += `?${queryString}`;
+
+  try {
+    // Fetch the audio from the URL
+    const response = await fetch(url);
+
+    if (!response.ok) {
+      throw new Error(`Failed to generate audio: ${response.statusText}`);
+    }
+
+    // Get the audio data as an ArrayBuffer
+    const audioBuffer = await response.arrayBuffer();
+
+    // Convert the ArrayBuffer to a base64 string
+    const base64Data = Buffer.from(audioBuffer).toString('base64');
+
+    // Determine the mime type from the response headers or default to audio/mpeg
+    const contentType = response.headers.get('content-type') || 'audio/mpeg';
+
+    return {
+      data: base64Data,
+      mimeType: contentType,
+      metadata: {
+        prompt,
+        voice,
+        model: 'openai-audio',
+        seed,
+        voiceInstructions
+      }
+    };
+  } catch (error) {
+    console.error('Error generating audio:', error);
+    throw error;
+  }
+}
+
+
+
+/**
+ * List available audio voices
+ *
+ * @returns {Promise<Object>} - Object containing the list of available voice options
+ */
+export async function listAudioVoices() {
+  // Return the complete list of available voices
+  const voices = [
+    "alloy",
+    "echo",
+    "fable",
+    "onyx",
+    "nova",
+    "shimmer",
+    "coral",
+    "verse",
+    "ballad",
+    "ash",
+    "sage",
+    "amuch",
+    "dan"
+  ];
+
+  return { voices };
+}

src/services/imageSchema.js

@@ -0,0 +1,111 @@
+/**
+ * Schema definitions for the Pollinations Image API
+ */
+
+/**
+ * Schema for the generateImageUrl tool
+ */
+export const generateImageUrlSchema = {
+  name: 'generateImageUrl',
+  description: 'Generate an image URL from a text prompt',
+  inputSchema: {
+    type: 'object',
+    properties: {
+      prompt: {
+        type: 'string',
+        description: 'The text description of the image to generate'
+      },
+      model: {
+        type: 'string',
+        description: 'Model name to use for generation (default: "flux"). Available options: "flux", "sdxl", "sd3", "sd15", "flux-schnell", "flux-dev"'
+      },
+      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)'
+      }
+    },
+    required: ['prompt']
+  }
+};
+
+/**
+ * Schema for the generateImage tool
+ */
+export const generateImageSchema = {
+  name: 'generateImage',
+  description: 'Generate an image, return the base64-encoded data, and save to a file by default',
+  inputSchema: {
+    type: 'object',
+    properties: {
+      prompt: {
+        type: 'string',
+        description: 'The text description of the image to generate'
+      },
+      model: {
+        type: 'string',
+        description: 'Model name to use for generation (default: "flux"). Available options: "flux, "turbo" (sdxl),'
+      },
+      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: "./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']
+  }
+};
+
+/**
+ * Schema for the listImageModels tool
+ */
+export const listImageModelsSchema = {
+  name: 'listImageModels',
+  description: 'List available image models',
+  inputSchema: {
+    type: 'object',
+    properties: {}
+  }
+};

src/services/imageService.js

@@ -0,0 +1,200 @@
+/**
+ * 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;
+  }
+}

src/services/textSchema.js

@@ -0,0 +1,41 @@
+/**
+ * Schema definitions for the Pollinations Text API
+ */
+
+/**
+ * Schema for the respondText tool
+ */
+export const respondTextSchema = {
+  name: 'respondText',
+  description: 'Respond with text to a prompt using the Pollinations Text API',
+  inputSchema: {
+    type: 'object',
+    properties: {
+      prompt: {
+        type: 'string',
+        description: 'The text prompt to generate a response for'
+      },
+      model: {
+        type: 'string',
+        description: 'Model to use for text generation (default: "openai"). Available options: "openai", "anthropic", "mistral", "llama", "gemini" - use listTextModels to see all models'
+      },
+      seed: {
+        type: 'number',
+        description: 'Seed for reproducible results (default: random)'
+      }
+    },
+    required: ['prompt']
+  }
+};
+
+/**
+ * Schema for the listTextModels tool
+ */
+export const listTextModelsSchema = {
+  name: 'listTextModels',
+  description: 'List available text models',
+  inputSchema: {
+    type: 'object',
+    properties: {}
+  }
+};

src/services/textService.js

@@ -0,0 +1,73 @@
+/**
+ * Pollinations Text Service
+ *
+ * Functions for interacting with the Pollinations Text API
+ */
+
+/**
+ * Responds with text to a prompt using the Pollinations Text API
+ *
+ * @param {string} prompt - The text prompt to generate a response for
+ * @param {string} [model="openai"] - Model to use for text generation. Available options: "openai", "anthropic", "mistral", "llama", "gemini"
+ * @param {number} [seed] - Seed for reproducible results (default: random)
+ * @returns {Promise<string>} - The generated text response
+ */
+export async function respondText(prompt, model = "openai", seed = Math.floor(Math.random() * 1000000)) {
+  if (!prompt || typeof prompt !== 'string') {
+    throw new Error('Prompt is required and must be a string');
+  }
+
+  // Build the query parameters
+  const queryParams = new URLSearchParams();
+  if (model) queryParams.append('model', model);
+  if (seed !== undefined) queryParams.append('seed', seed);
+
+  // Construct the URL
+  const encodedPrompt = encodeURIComponent(prompt);
+  const baseUrl = 'https://text.pollinations.ai';
+  let url = `${baseUrl}/${encodedPrompt}`;
+
+  // Add query parameters if they exist
+  const queryString = queryParams.toString();
+  if (queryString) {
+    url += `?${queryString}`;
+  }
+
+  try {
+    // Fetch the text from the URL
+    const response = await fetch(url);
+
+    if (!response.ok) {
+      throw new Error(`Failed to generate text: ${response.statusText}`);
+    }
+
+    // Get the text response
+    const textResponse = await response.text();
+
+    return textResponse;
+  } catch (error) {
+    console.error('Error generating text:', error);
+    throw error;
+  }
+}
+
+/**
+ * List available text generation models from Pollinations API
+ *
+ * @returns {Promise<Object>} - Object containing the list of available text models
+ */
+export async function listTextModels() {
+  try {
+    const response = await fetch('https://text.pollinations.ai/models');
+
+    if (!response.ok) {
+      throw new Error(`Failed to list text models: ${response.statusText}`);
+    }
+
+    const models = await response.json();
+    return { models };
+  } catch (error) {
+    console.error('Error listing text models:', error);
+    throw error;
+  }
+}