get_stock_value
Retrieve stock valuation analysis data for Chinese stocks by providing the stock symbol to assess investment value and performance metrics.
Instructions
获取指定股票的个股估值分析数据
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | Yes | 股票代码 (例如: '000001') | |
| output_format | No | 输出数据格式: json, csv, xml, excel, markdown, html。默认: markdown | markdown |
Implementation Reference
- src/china_stock_mcp/server.py:891-893 (registration)Registers the 'get_stock_value' tool using the @mcp.tool decorator.@mcp.tool( name="get_stock_value", description="获取指定股票的个股估值分析数据" )
- src/china_stock_mcp/server.py:894-906 (handler)The handler function that fetches the stock valuation data using ak.stock_value_em(symbol), handles empty DataFrame, and returns formatted output.def get_stock_value( symbol: Annotated[str, Field(description="股票代码 (例如: '000001')")], output_format: Annotated[ Literal["json", "csv", "xml", "excel", "markdown", "html"], Field(description="输出数据格式: json, csv, xml, excel, markdown, html。默认: markdown"), ] = "markdown" ) -> str: """获取指定股票的个股估值分析数据.""" df = ak.stock_value_em(symbol=symbol) if df.empty: df = pd.DataFrame() return _format_dataframe_output(df, output_format)
- Pydantic schema definitions for input parameters: symbol (str) and output_format (Literal with default).symbol: Annotated[str, Field(description="股票代码 (例如: '000001')")], output_format: Annotated[ Literal["json", "csv", "xml", "excel", "markdown", "html"], Field(description="输出数据格式: json, csv, xml, excel, markdown, html。默认: markdown"), ] = "markdown"
- src/china_stock_mcp/server.py:89-118 (helper)Helper function to format the DataFrame output in various formats: json, csv, etc., used by get_stock_value.def _format_dataframe_output( df: pd.DataFrame, output_format: Literal["json", "csv", "xml", "excel", "markdown", "html"], ) -> str: """ 根据指定的格式格式化 DataFrame 输出。 """ if df.empty: return json.dumps([]) if output_format == "json": return df.to_json(orient="records", force_ascii=False) elif output_format == "csv": return df.to_csv(index=False) elif output_format == "xml": return df.to_xml(index=False) elif output_format == "excel": # 使用 BytesIO 将 Excel 写入内存 output = io.BytesIO() df.to_excel(output, index=False, engine='openpyxl') # 返回 base64 编码的二进制数据，或者直接返回字节流 # 为了兼容性，这里尝试返回 utf-8 编码的字符串，但对于二进制文件，通常直接传输字节流更合适 return output.getvalue().decode("utf-8", errors="ignore") elif output_format == "markdown": return df.to_markdown(index=False) elif output_format == "html": return df.to_html(index=False) else: return df.to_json(orient="records", force_ascii=False)