Stock Info (AKShare)

🚀 Stock Information Service Center

This is a stock data service based on FastMCP, offering functions such as historical stock price data, company fundamental information, and news.

🚀 Quick Start

Prerequisites

• Python version: 3.10 or higher
• Dependencies:
  • fastmcp
  • akshare
  • pandas
  • pydantic
  • pydantic-settings

Installation and Deployment

1. Create a virtual environment:

python -m venv .venv

2. Activate the virtual environment:

   • On Windows: .venv\Scripts\activate
   • On Linux/macOS: source .venv/bin/activate

3. Install dependencies:

pip install -r requirements.txt

Starting the Service

1. Start with default configuration:

python src/server.py

2. Start using the HTTP protocol:

uvicorn stock_info.app:app --reload

✨ Features

• Retrieve historical stock data
• Query basic stock information
• Obtain a list of risk - warning stocks
• View individual stock news
• Get financial news (supports pagination)
• Retrieve information on a stock's main business
• .....More features will be added gradually

📦 Installation

MCP Client Configuration Steps

1. Pull the code.
2. Create a virtual environment using uv, requiring Python version 3.10 or higher.
3. Configure the MCP service using the local directory method.

Here is an example configuration:

{
  "mcpServers": {
    "stock - info": {
      "isActive": true,
      "command": "uv",
      "args": [
        "--directory",
        "\\path\\to\\sock_info\\src",
        "run",
        "server.py"
      ]
    }
  }
}

💻 Usage Examples

Basic Usage

Here are some main functions provided by the service and their purposes:

• Retrieve historical stock data: get_stock_history_data() Returns the historical stock price data of the specified stock.

• Query basic stock information: get_stock_info() Returns the basic information of the stock, such as the company name and industry.

• List of risk - warning stocks: get_risk_warning_stocks() Obtains the list of stocks currently under risk warning.

• View individual stock news: get_stock_news() Retrieves relevant news about the specified stock.

• Financial news (supports pagination): get_financial_news() Returns the latest financial news and supports pagination queries.

• Retrieve information on a stock's main business: get_main_business_info() Returns the details of the stock's main business.

📚 Documentation

Project Structure

stock - info/
├── src/
│   ├── config/           # Configuration management
│   │   └── settings.py
│   ├── core/            # Core functions
│   │   └── exceptions.py
│   ├── models/          # Data models
│   │   └── stock.py
│   ├── repository/      # Data access layer
│   │   └── stock_repository.py
│   ├── service/         # Business logic layer
│   │   └── stock_service.py
│   └── server.py        # Service entry
├── pyproject.toml       # Project configuration
└── README.md           # Project documentation

Project Characteristics

1. Modular Design: The code structure is clear, facilitating maintenance and expansion.
2. Unified Exception Handling: A unified error capture and handling mechanism is implemented through exceptions.py.
3. Data Access Layer: The repository layer is used to encapsulate data operations, enhancing code reusability.
4. Dependency Management: Project dependencies are managed through pyproject.toml and requirements.txt to ensure environment consistency.

Development Specifications

1. Follow the PEP 8 coding standard to maintain a unified code style.
2. Use black for code formatting to ensure code readability.
3. Use the ruff tool for code inspection and linting to guarantee code quality.
4. Before submitting code, run test cases and ensure all checks pass.

Error Handling

When the service encounters an error, it returns a JSON - formatted response as follows:

{
  "error": {
    "code": " ErrorCode ",
    "message": " Error Message "
  }
}

Here are the main error codes and their corresponding meanings:

• 400: Bad Request
• 401: Unauthorized
• 403: Forbidden
• 404: Not Found
• 500: Internal Server Error

Notes

⚠️ Important Note

All API interfaces support JSON - formatted responses, and some interfaces also support pagination queries.

💡 Usage Tip

Read the interface documentation carefully before use to ensure correct use of parameters and return values. Be aware that the service may incur certain overhead during operation, so configure resource limits according to actual circumstances.