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

Installing via Smithery

To install mcpollinations for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @pinkpixel-dev/mcpollinations --client claude

The easiest way to use the MCP server:

# Run directly with npx (no installation required)
npx @pinkpixel/mcpollinations

If you prefer to install it globally:

# Install globally
npm install -g @pinkpixel/mcpollinations

# Run the server
mcpollinations
# or
npx @pinkpixel/mcpollinations

Or clone the repository:

# 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:

# If installed globally
npx @pinkpixel/mcpollinations generate-config

# Or run directly
node /path/to/MCPollinations/generate-mcp-config.js

Quick MCP Config (env)

If you prefer to skip the generator, copy this into your MCP client config:

{
  "mcpollinations": {
    "command": "npx",
    "args": ["-y", "@pinkpixel/mcpollinations"],
    "env": {
      "token": "YOUR_TOKEN_OPTIONAL",
      "referrer": "your-app-or-domain-optional",
      "IMAGE_MODEL": "flux",
      "IMAGE_WIDTH": "1024",
      "IMAGE_HEIGHT": "1024",
      "IMAGE_ENHANCE": "true",
      "IMAGE_SAFE": "false",
      "TEXT_MODEL": "openai",
      "TEXT_TEMPERATURE": "0.7",
      "TEXT_TOP_P": "0.9",
      "TEXT_SYSTEM": "",
      "AUDIO_VOICE": "alloy",
      "OUTPUT_DIR": "./mcpollinations-output"
    }
  }
}

1. Follow the prompts to customize your configuration or use the defaults.

   • Set an output directory (relative paths recommended for portability)
     • Windows users: Consider using absolute paths (e.g., C:\Users\YourName\Pictures\MCPollinations) for more reliable file saving
   • Configure optional authentication (token, referrer) under env
   • 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)

2. Copy the generated mcp.json file to your application's MCP settings .json file.

3. Restart your application.

After integration, you can use commands like:

"Generate an image of a sunset over the ocean using MCPollinations"

Authentication (Optional)

MCPollinations supports optional authentication to provide access to more models and better rate limits. The server works perfectly without authentication (free tier), but users with API tokens can get enhanced access.

Configuration Methods

Method 1: Environment Variables (Recommended for security)

# Set environment variables before running the server
export POLLINATIONS_TOKEN="your-api-token"
export POLLINATIONS_REFERRER="https://your-domain.com"

# Then run the server
npx @pinkpixel/mcpollinations

Method 2: MCP Configuration File (env) When generating your MCP configuration, place auth inside env so your MCP client passes them as environment variables to the server process:

{
  "mcpollinations": {
    "command": "npx",
    "args": ["-y", "@pinkpixel/mcpollinations"],
    "env": {
      "token": "your-api-token",
      "referrer": "your-app-or-domain"
    }
  }
}

You can also provide POLLINATIONS_TOKEN and POLLINATIONS_REFERRER instead; the server recognizes both forms. Using token and referrer inside env is recommended for MCP configs.

Authentication Parameters

• token (optional): Your Pollinations API token for enhanced access
• referrer (optional): Your domain/application referrer URL

Both parameters are completely optional. Leave them empty or unset to use the free tier.

Using Your Configuration Settings

MCPollinations respects your MCP configuration settings placed in env as defaults. When you ask an AI assistant to generate content:

• Your configured models, output directories, and parameters are used automatically
• To override: Specifically instruct the AI to use different settings
  • "Generate an image using the kontext model"
  • "Save this image to my Desktop folder"
  • "Use a temperature of 1.2 for this text generation"

Example Instructions:

• ✅ "Generate a sunset image" → Uses your configured model and output directory
• ✅ "Generate a sunset image with the flux model" → Overrides model only
• ✅ "Generate a sunset image and save it to C:\Pictures" → Overrides output path only

This ensures your preferences are always respected unless you specifically want different settings for a particular request.

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:

   npm install -g @pinkpixel/mcpollinations
   # Run with npx
   npx @pinkpixel/mcpollinations
   

3. Install AbortController manually:

   • If for some reason the polyfill doesn't work:

   npm install node-abort-controller
   

Check Your Node.js Version

To check your current Node.js version:

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:

Image Generation 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. editImage - NEW! Edit or modify existing images based on text prompts
4. generateImageFromReference - NEW! Generate new images using existing images as reference
5. listImageModels - Lists available models for image generation

Text & Audio Tools

1. respondText - Responds with text to a prompt using text models (customizable parameters)
2. respondAudio - Generates an audio response to a text prompt (customizable voice parameter)
3. listTextModels - Lists available models for text generation
4. listAudioVoices - Lists all available voices for audio generation

Text Generation Details

Available Parameters

The respondText tool supports several parameters for fine-tuning text generation:

• model: Choose from available text models (use listTextModels to see current options)
• temperature (0.0-2.0): Controls randomness in the output
  • Lower values (0.1-0.7) = more focused and deterministic
  • Higher values (0.8-2.0) = more creative and random
• top_p (0.0-1.0): Controls diversity via nucleus sampling
  • Lower values = more focused on likely tokens
  • Higher values = considers more token possibilities
• system: System prompt to guide the model's behavior and personality

Customizing Text Generation

// Example options for respondText
const options = {
  model: "openai",           // Model selection
  temperature: 0.7,          // Balanced creativity
  top_p: 0.9,               // High diversity
  system: "You are a helpful assistant that explains things clearly and concisely."
};

Configuration Examples

In your MCP configuration, set defaults under env so the server uses them automatically:

{
  "mcpollinations": {
    "env": {
      "TEXT_MODEL": "openai",
      "TEXT_TEMPERATURE": "0.7",
      "TEXT_TOP_P": "0.9",
      "TEXT_SYSTEM": "You are a helpful coding assistant."
    }
  }
}

Image-to-Image Generation (NEW!)

MCPollinations now supports powerful image-to-image generation with two specialized tools:

editImage Tool

Perfect for modifying existing images:

• Remove objects: "remove the cat from this image"
• Add elements: "add a dog to this scene"
• Change backgrounds: "replace the background with mountains"
• Style modifications: "make the lighting more dramatic"

generateImageFromReference Tool

Perfect for creating variations and new styles:

• Style transfer: "make this photo look like a painting"
• Format changes: "convert this to a cartoon style"
• Creative variations: "create a futuristic version of this"
• Artistic interpretations: "make this look like a sketch"

Supported Models

• kontext: Specialized model optimized for image-to-image tasks
• nanobanana: New Google model supporting both text-to-image and image-to-i

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