bqmcp-cloud 0.1.5

A cloud service for document processing and AI content generation, built on top of FastMCP

BQMCP Cloud

A cloud service for document processing and AI content generation, built on top of FastMCP.

Features

• PDF document processing and content extraction
• AI-powered content generation:
  • PPT generation
  • Title generation
  • Abstract generation
  • Quick read content
  • Mind map generation
  • Deep reading content
  • Release date extraction
  • PDF generation

Installation

pip install bqmcp-cloud

Usage

As a Python Package

from bqmcp_cloud import BQMCPCloud

# Initialize the cloud service
cloud = BQMCPCloud(
    api_key="your-openai-api-key",  # or set OPENAI_API_KEY environment variable
    proxy="your-proxy-url",         # or set HTTP_PROXY environment variable
    base_output_path="outputs",     # optional
    log_level="INFO",              # optional
    mcp_name="bigquant"            # optional
)

# Run the server
cloud.run(transport='stdio')  # or 'http'

Command Line Interface

# Basic usage
bqmcp-cloud

# With custom configuration
bqmcp-cloud --api-key "your-key" --proxy "your-proxy" --output-dir "custom-outputs" --log-level DEBUG

Configuration

The service can be configured through:

1. Environment variables:

   • OPENAI_API_KEY: Your OpenAI API key
   • HTTP_PROXY: HTTP proxy URL

2. Constructor parameters:

   • api_key: OpenAI API key
   • proxy: HTTP proxy URL
   • base_output_path: Base directory for output files
   • log_level: Logging level (DEBUG, INFO, WARNING, ERROR, CRITICAL)
   • mcp_name: Name for the MCP server

3. Command line arguments:

   • --api-key: OpenAI API key
   • --proxy: HTTP proxy URL
   • --output-dir: Base output directory
   • --log-level: Logging level
   • --name: MCP server name
   • --transport: Transport type (stdio or http)

Development

1. Clone the repository:

git clone https://github.com/yourusername/bqmcp-cloud.git
cd bqmcp-cloud

2. Create a virtual environment:

python -m venv .venv
source .venv/bin/activate  # Linux/Mac
# or
.venv\Scripts\activate     # Windows

3. Install development dependencies:

pip install -e ".[dev]"

4. Run tests:

pytest

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.