AI看线 - A股技术分析与AI预测工具

by QuantML-Github

333 stars

1.2k downloads

Not rated

GitHub

Finance

About

Python-based stock analysis tool that combines traditional technical analysis with AI prediction capabilities. Providing comprehensive stock analysis and forecasting using K-line charts, technical indicators, financial data, and news data. With CMD/WEB/MCP supported.

Details

Author: QuantML-Github
GitHub stars: 333
Downloads: 1,220
Categories: Finance

- 使用AKShare获取A股历史交易、财务和新闻数据
- 计算MA、MACD、KDJ、RSI、布林带等多种技术指标
- 生成静态PNG和交互式HTML K线图及技术指标图表
- 利用多模态AI（如通义千问视觉模型）分析历史数据并预测走势
- 提供简洁美观的Web界面进行交互式分析
- 支持MCP协议，通过LLM自然语言交互随时分析股票

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name AI看线 - A股技术分析与AI预测工具

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "ai\u770b\u7ebf - a\u80a1\u6280\u672f\u5206\u6790\u4e0eai\u9884\u6d4b\u5de5\u5177": {
            "AI-Kline": {
                "command": "python",
                "args": [
                    "main.py",
                    "--stock_code",
                    "000001",
                    "--period",
                    "1\u5e74",
                    "--save_path",
                    "./output"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ai\u770b\u7ebf - a\u80a1\u6280\u672f\u5206\u6790\u4e0eai\u9884\u6d4b\u5de5\u5177": {
            "AI-Kline": {
                "command": "python",
                "args": [
                    "main.py",
                    "--stock_code",
                    "000001",
                    "--period",
                    "1\u5e74",
                    "--save_path",
                    "./output"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ai\u770b\u7ebf - a\u80a1\u6280\u672f\u5206\u6790\u4e0eai\u9884\u6d4b\u5de5\u5177": {
            "AI-Kline": {
                "command": "python",
                "args": [
                    "main.py",
                    "--stock_code",
                    "000001",
                    "--period",
                    "1\u5e74",
                    "--save_path",
                    "./output"
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "ai\u770b\u7ebf - a\u80a1\u6280\u672f\u5206\u6790\u4e0eai\u9884\u6d4b\u5de5\u5177": {
            "AI-Kline": {
                "command": "python",
                "args": [
                    "main.py",
                    "--stock_code",
                    "000001",
                    "--period",
                    "1\u5e74",
                    "--save_path",
                    "./output"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ai\u770b\u7ebf - a\u80a1\u6280\u672f\u5206\u6790\u4e0eai\u9884\u6d4b\u5de5\u5177": {
            "AI-Kline": {
                "command": "python",
                "args": [
                    "main.py",
                    "--stock_code",
                    "000001",
                    "--period",
                    "1\u5e74",
                    "--save_path",
                    "./output"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ai\u770b\u7ebf - a\u80a1\u6280\u672f\u5206\u6790\u4e0eai\u9884\u6d4b\u5de5\u5177": {
            "AI-Kline": {
                "command": "python",
                "args": [
                    "main.py",
                    "--stock_code",
                    "000001",
                    "--period",
                    "1\u5e74",
                    "--save_path",
                    "./output"
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "ai\u770b\u7ebf - a\u80a1\u6280\u672f\u5206\u6790\u4e0eai\u9884\u6d4b\u5de5\u5177": {
            "AI-Kline": {
                "command": "python",
                "args": [
                    "main.py",
                    "--stock_code",
                    "000001",
                    "--period",
                    "1\u5e74",
                    "--save_path",
                    "./output"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ai\u770b\u7ebf - a\u80a1\u6280\u672f\u5206\u6790\u4e0eai\u9884\u6d4b\u5de5\u5177": {
            "AI-Kline": {
                "command": "python",
                "args": [
                    "main.py",
                    "--stock_code",
                    "000001",
                    "--period",
                    "1\u5e74",
                    "--save_path",
                    "./output"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ai\u770b\u7ebf - a\u80a1\u6280\u672f\u5206\u6790\u4e0eai\u9884\u6d4b\u5de5\u5177": {
            "AI-Kline": {
                "command": "python",
                "args": [
                    "main.py",
                    "--stock_code",
                    "000001",
                    "--period",
                    "1\u5e74",
                    "--save_path",
                    "./output"
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "ai\u770b\u7ebf - a\u80a1\u6280\u672f\u5206\u6790\u4e0eai\u9884\u6d4b\u5de5\u5177": {
            "AI-Kline": {
                "command": "python",
                "args": [
                    "main.py",
                    "--stock_code",
                    "000001",
                    "--period",
                    "1\u5e74",
                    "--save_path",
                    "./output"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ai\u770b\u7ebf - a\u80a1\u6280\u672f\u5206\u6790\u4e0eai\u9884\u6d4b\u5de5\u5177": {
            "AI-Kline": {
                "command": "python",
                "args": [
                    "main.py",
                    "--stock_code",
                    "000001",
                    "--period",
                    "1\u5e74",
                    "--save_path",
                    "./output"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ai\u770b\u7ebf - a\u80a1\u6280\u672f\u5206\u6790\u4e0eai\u9884\u6d4b\u5de5\u5177": {
            "AI-Kline": {
                "command": "python",
                "args": [
                    "main.py",
                    "--stock_code",
                    "000001",
                    "--period",
                    "1\u5e74",
                    "--save_path",
                    "./output"
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "ai\u770b\u7ebf - a\u80a1\u6280\u672f\u5206\u6790\u4e0eai\u9884\u6d4b\u5de5\u5177": {
            "AI-Kline": {
                "command": "python",
                "args": [
                    "main.py",
                    "--stock_code",
                    "000001",
                    "--period",
                    "1\u5e74",
                    "--save_path",
                    "./output"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ai\u770b\u7ebf - a\u80a1\u6280\u672f\u5206\u6790\u4e0eai\u9884\u6d4b\u5de5\u5177": {
            "AI-Kline": {
                "command": "python",
                "args": [
                    "main.py",
                    "--stock_code",
                    "000001",
                    "--period",
                    "1\u5e74",
                    "--save_path",
                    "./output"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ai\u770b\u7ebf - a\u80a1\u6280\u672f\u5206\u6790\u4e0eai\u9884\u6d4b\u5de5\u5177": {
            "AI-Kline": {
                "command": "python",
                "args": [
                    "main.py",
                    "--stock_code",
                    "000001",
                    "--period",
                    "1\u5e74",
                    "--save_path",
                    "./output"
                ]
            }
        }
    }
}

From the repository

支持三种使用方式：命令行运行python main.py --stock_code 000001；启动Web服务python web_app.py后访问http://localhost:5000输入股票代码；或通过MCP Server（uv run mcp_server.py）在LLM客户端配置streamable-http端点http://localhost:8000/mcp交互分析。

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "ai\u770b\u7ebf - a\u80a1\u6280\u672f\u5206\u6790\u4e0eai\u9884\u6d4b\u5de5\u5177": {
            "AI-Kline": {
                "command": "python",
                "args": [
                    "main.py",
                    "--stock_code",
                    "000001",
                    "--period",
                    "1\u5e74",
                    "--save_path",
                    "./output"
                ]
            }
        }
    }
}

McpServers

{
    "AI-Kline": {
        "command": "python",
        "args": [
            "main.py",
            "--stock_code",
            "000001",
            "--period",
            "1\u5e74",
            "--save_path",
            "./output"
        ]
    }
}

# AI看线 - 股票技术分析与AI预测工具（AI-Kline - Stock Technical Analysis and AI Prediction Tool） <div align="center">  <a href="README_EN.md">English</a> | <a href="README.md">中文</a> </div> ## 项目简介 AI看线是一个基于Python的A股分析工具，结合了传统技术分析和人工智能预测功能。利用K线图，技术指标，财务数据，新闻数据对股票进行全面分析及预测。该工具可以： 1. 获取A股股票的历史量价数据并计算各种技术指标 2. 生成专业的K线图和技术指标可视化图表 3. 获取股票相关的财务数据和新闻信息 4. 使用openai api分析整合数据并预测股票未来走势 ## 功能特点 - **数据获取**：使用AKShare获取A股股票的历史交易数据、财务数据和新闻信息 - **技术分析**：计算多种技术指标，包括MA、MACD、KDJ、RSI、布林带等 - **可视化**：生成静态和交互式K线图及技术指标图表 - **AI分析**：利用多模态AI分析股票数据并预测未来走势 - **Web界面**：提供简洁美观的Web界面，方便用户输入股票代码查看分析结果 - **MCP SERVER**：提供MCP SERVER支持，支持通过LLM交互，随时分析股票 ## 安装说明 ### 环境要求 - Python 3.8+ - 依赖包：见`requirements.txt` ### 安装步骤 1. 克隆或下载本项目到本地 2. 安装依赖包 ```bash pip install -r requirements.txt ``` 3. 创建`.env`文件，添加API密钥 ``` API_KEY=your_api_key_here BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1 MODEL_NAME=qwen-vl-max ``` > 注意：需使用多模态模型 ## 使用方法 ### 命令行使用 ```bash python main.py --stock_code 000001 --period 1年 --save_path ./output ``` 参数说明： - `--stock_code`：股票代码，必填参数 - `--period`：分析周期，可选值："1年"、"6个月"、"3个月"、"1个月"，默认为"1年" - `--save_path`：结果保存路径，默认为"./output" ### Web界面使用启动Web服务： ```bash python web_app.py ``` 然后在浏览器中访问 http://localhost:5000 即可使用Web界面： 1. 在表单中输入股票代码（例如：000001） 2. 选择分析周期 3. 点击"开始分析"按钮 4. 等待分析完成后查看结果 Web界面包括以下内容： - 股票基本信息 - K线图和技术指标图表 - AI分析结果文本页面截图： ![Web界面截图](static/images/image.png) ### MCP SERVER使用启动mcp： ```bash uv run mcp_server.py ``` 然后在mcp客户端中配置（streamable-http）： http://localhost:8000/mcp Cherry-Studio页面截图： ![MCP界面截图](static/images/mcp1.png) ![MCP界面截图](static/images/mcp2.png) ### 输出结果程序运行后将在指定的保存路径下生成： 1. K线图和技术指标图表（静态PNG图片和交互式HTML图表） 2. AI分析结果文本文件 ## 项目结构 ``` AI看线/ ├── main.py # 主程序入口 ├── web_app.py # Web应用入口 ├── requirements.txt # 依赖包列表 ├── .env # 环境变量配置（需自行创建） ├── modules/ # 功能模块 │ ├── __init__.py │ ├── data_fetcher.py # 数据获取模块 │ ├── technical_analyzer.py # 技术分析模块 │ ├── visualizer.py # 可视化模块 │ └── ai_analyzer.py # AI分析模块 ├── templates/ # Web模板目录 │ └── index.html # 主页模板 ├── static/ # 静态资源目录 │ ├── css/ # CSS样式 │ │ └── style.css # 自定义样式 │ └── js/ # JavaScript脚本 │ └── main.js # 主要脚本 └── output/ # 输出结果目录（运行时自动创建） ├── charts/ # 图表目录 └── *_analysis_result.txt # 分析结果文件 ``` ## 交流学习 ![加群](static/images/yzbjs1.png) ## 注意事项 - 本工具仅供学习和研究使用，不构成任何投资建议 - AI分析结果基于历史数据和当前信息，不能保证未来走势的准确性 - 使用前请确保已正确配置Gemini API密钥 - 股票数据获取依赖于AKShare库，可能受到网络和数据源的限制 - 本项目为QuantML开源项目，转载或使用需注明出处，商业使用请联系微信号QuantML ## 免责声明本工具提供的分析和预测仅供参考，不构成任何投资建议。投资有风险，入市需谨慎。用户应对自己的投资决策负责。

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AI看线 - A股技术分析与AI预测工具

About

Details

Jump to

Setting up with Highlight

Setting up with Cursor

JSON

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Setting up with Claude Desktop

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JSON

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Setting up with Windsurf

JSON

JSON

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Setting up with Cline

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Setting up with Goose

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JSON

From the repository

Claude Desktop / Cursor

McpServers

Install

About

Details

Jump to

Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

Install

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