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A Python package for technical analysis of financial markets

Project description

技术指标分析工具

该工具提供mcp服务器用于分析ETF和股票的技术指标。它使用akshare库获取历史数据,并计算RSI、布林带和移动平均线等技术指标。该工具支持ETF和股票历史数据分析。

API文档

mcp服务器提供的接口:

analyze_etf_technical

@mcp.tool()
def analyze_etf_technical(etf_code='510300', with_market_style=False):
    """
    ETF技术指标分析工具
    :param etf_code: ETF代码 (例如'510300')
    :param with_market_style: 是否包含市场风格分类 (True/False)
    :param base_date: 基准日期,格式为YYYYMMDD (可选)
    :return: 包含技术指标的Markdown表格(最后5条记录)
    """

新增字段说明:

参数:

  • etf_code: ETF代码,默认为'510300'(沪深300ETF)

返回值:

  • 包含以下技术指标的Markdown表格:
    • 价格数据
    • RSI指标
    • 布林带
    • 移动平均线
    • atr: 平均真实波幅(10日),衡量价格波动性的指标,数值越大表示波动越大
    • mkt_style: 市场风格分类结果

示例:

result = analyze_etf_technical('510300')
print(result)

analyze_stock_hist_technical

@mcp.tool()
def analyze_stock_hist_technical(stock_code='000001'):
    """
    股票历史数据技术指标分析工具
    :param stock_code: 股票代码 (例如'000001')
    :param base_date: 基准日期,格式为YYYYMMDD (可选)
    :return: 包含技术指标的Markdown表格(最后5条记录)
    """

参数:

  • stock_code: 股票代码,默认为'000001'(平安银行)

返回值:

  • 包含以下技术指标的Markdown表格:
    • 价格数据
    • RSI指标
    • 布林带
    • 移动平均线
    • atr: 平均真实波幅(10日),衡量价格波动性的指标,数值越大表示波动越大
    • mkt_style: 市场风格分类结果

示例:

result = analyze_stock_hist_technical('000001')
print(result)

安装与配置

安装

pip install technical-analysis-mcp

配置

  1. 确保已安装Python 3.8+版本
  2. 需要配置akshare数据源(可选)
  3. 运行MCP服务器:
technical-analysis-mcp

市场风格分类示例

# 获取带市场风格分类的ETF技术指标
result = analyze_etf_technical('510300', with_market_style=True)
print(result)

# 获取带市场风格分类的股票技术指标
result = analyze_stock_hist_technical('000001', with_market_style=True)
print(result)

MCP配置示例

{
  "mcpServers": {
    "technical-analysis-mcp": {
      "command": "uvx",
      "args": ["technical-analysis-mcp"]
    }
  }
}

Restful API

使用uvicorn启动FastAPI应用:

uvicorn technical_analysis.http:app --reload --port 8000

应用启动后,可以通过以下地址访问API文档: http://localhost:8000/docs

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