Qiniu MCP Server 1nk

🚀 Qiniu Cloud MCP Server

A Model Context Protocol (MCP) server built on Qiniu Cloud products, enabling users to interact with Qiniu Cloud services within the context of AI large model clients. This server supports Qiniu Cloud Storage (Kodo), intelligent multimedia processing, and Content Delivery Network (CDN) functionalities.

🚀 Quick Start

A Model Context Protocol (MCP) server built on Qiniu Cloud products supports user interaction with Qiniu Cloud services in the context of an AI large model client. This server offers support for Qiniu Cloud Storage (Kodo), intelligent multimedia processing, and Content Delivery Network (CDN) capabilities.

✨ Features

• Storage: Supports file upload, download, deletion, and listing operations.
• Intelligent Multimedia: Provides functions such as image scaling, format conversion, and watermark addition.
• CDN: Enables efficient distribution of static resources, enhancing content delivery speed.

📦 Installation

Software Environment

• Python Version: It is recommended to use Python 3.8 or a higher version.
• uv Package Manager: Used for unified management and running of services, which is included in the project by default.

Operating System

• Supports Linux (recommended) and macOS. Additional configuration is required for the Windows platform.

Install Dependencies

1. Clone the code repository:

   git clone https://github.com/qiniu/mcp-server.git
   cd mcp-server
   

2. Install project dependencies:

   uv pip install -e .
   

3. Configure environment variables: Copy and modify the env.example file, and fill in the real Qiniu Cloud credentials and region information.

Run the Server

1. Run in the project root directory:

   uv --directory . run qiniu-mcp-server
   

2. Enable debug mode:

   uv --directory . run qiniu-mcp-server --debug
   

💻 Usage Examples

Upload a File to the Bucket

import qiniu

# Initialize Qiniu Cloud configuration
config = qiniu.Config(
    access_key='your_access_key',
    secret_key='your_secret_key',
    region=Region.region_z0()
)

# Create a storage instance
bucket = qiniu.Bucket(config, 'your_bucket_name')

# Upload a file
with open('file.jpg', 'rb') as f:
    res = bucket.put_stream('target.jpg', f)

Process Multimedia Resources

from qiniuImagePathProcessor import ImageProcessor

processor = ImageProcessor(access_key='...', secret_key='...')
processed_image = processor.resize('original.jpg', width=800, height=600)

📚 Documentation

New Feature Modules

Create a new business package in the core/storage directory and add utility classes and resource extension files as needed.

Register Custom Tools

Define the loading function in the __init__.py of the business package and register it uniformly in core/__init__.py.

🔧 Technical Details

Testing with the Inspector Tool

1. Install and run the Inspector:

   npm install -g @modelcontextprotocol/inspector
   inspector run qiniu-mcp-server
   

2. Verify the interface response to ensure that all operations meet expectations.

Common Issues

1. How to handle upload failures?

   • Check the network connection and Qiniu Cloud credential configuration.

2. What if multimedia processing is slow?

   • Ensure that the Qiniu Cloud account has sufficient processing quotas.

3. What if the CDN acceleration effect is not obvious?

   • Check the CDN configuration to ensure that the domain name and certificate are correctly configured.