Mcpollinations

🚀 MCPollinations MCP Server

MCPollinations is a multi - process computing framework based on the Model Context Protocol (MCP), aiming to enhance the performance of AI models in image generation and text processing. It significantly improves task execution efficiency through optimized resource allocation and parallel computing.

✨ Features

• Multi - process Architecture: Supports distributed computing to improve processing speed.
• Model Optimization: Incorporates multiple AI models suitable for different scenarios.
• Efficient Resource Management: Dynamically adjusts resource usage to ensure optimal performance.

📦 Installation

Installation Steps

1. Get the Source Code
   • Clone the repository via Git:

     git clone https://github.com/your-repository/mcpollinations.git
     

2. Install Dependencies
   • Install dependencies using the Node.js package manager:

     npm install
     

3. Start the Service
   • Start the MCP server:

     node index.js
     

Configuration Guide

• Environment Variable Configuration
  • Set NODE_ENV to production or development mode:

    export NODE_ENV=production
    

• Log Management
  • Configure the log output path and level:

    const logger = require('mcpollinations').logger;
    logger.setLevel('info');
    

💻 Usage Examples

Image Generation

Default Behavior

• Use the default model flux for image generation.
• The output format is PNG, and other formats such as JPEG and WEBP are also supported.

Custom Configuration

const options = {
  model: "stable-diffusion",
  width: 512,
  height: 512,
  seed: 456789,
  enhance: true,
  safe: true,
  saveToFile: true,
  outputPath: "/path/to/output",
  fileName: "custom_image",
  format: "jpeg"
};

Text Processing

• Supports multiple language models, such as GPT - 3 and BERT.
• Provides text summarization, translation, and generation functions.

🔧 Technical Details

Parallel Computing

• Supports multi - thread task scheduling to improve processing efficiency.
• Automatically balances the load to ensure reasonable resource allocation.

Plugin Extension

• Supports custom plugin development to extend the framework's functionality.
• Provides a rich set of API interfaces for easy integration.

Troubleshooting

Common Issues

• Service Startup Failure: Check if the dependencies are correctly installed and confirm that the port is not occupied.
• Poor Performance: Optimize the code logic and increase the memory configuration.

Log Analysis

• View real - time logs:

  tail -f logs/app.log
  

• Analyze error messages and fix issues.

📚 Documentation

Developer Guide

• Dependency Injection: Use a dependency injection container to manage the service lifecycle. Supports DI containers such as inversify and typedi.
• Unit Testing: Write unit test cases to ensure code quality. Use testing frameworks such as Jest or Mocha for testing.

Documentation Resources

• Official Documentation: Provides detailed user manuals and technical guides.
• Example Code: Demonstrates how to implement core functions.
• Community Support: Participate in developer forums and discussion groups to get help and share experiences.

FAQ

Question 1: How to install MCPollinations?

Answer: Please refer to the Installation Guide for operation.

Question 2: Which image formats are supported?

Answer: Currently, PNG, JPEG, and WEBP formats are supported, and more formats are coming soon.

Question 3: How to configure the log level?

Answer: Adjust the log output level by setting the logger.setLevel method.

🤝 Contribution Guide

• Code Contribution: Welcome to submit Pull Requests and participate in code development.
• Documentation Contribution: Help improve the project documentation to benefit more people.
• Issue Reporting: Submit bugs or feature requests in the Issues section.

Through the above content, you can comprehensively understand the functions and usage of MCPollinations. If you have any questions or need further assistance, please feel free to contact our support team.