get_profit_forecast
Retrieve profit forecast data for Chinese stocks, including projected annual net profit and earnings per share, to support investment analysis and decision-making.
Instructions
获取股票的业绩预测数据，包括预测年报净利润和每股收益
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | Yes | 股票代码 (例如: '600519') | |
| 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:695-717 (handler)The main handler function for the 'get_profit_forecast' tool. It takes a stock symbol and optional output format, fetches profit forecast data for '预测年报净利润' (predicted annual net profit) and '预测年报每股收益' (predicted annual EPS) using ak.stock_profit_forecast_ths from akshare, concatenates the DataFrames, and returns the formatted output.def get_profit_forecast( symbol: Annotated[str, Field(description="股票代码 (例如: '600519')")], 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: """ 获取股票的业绩预测数据。 """ supported_indicators = ["预测年报净利润", "预测年报每股收益"] df_list = [] for ind in supported_indicators: temp_df = ak.stock_profit_forecast_ths(symbol=symbol, indicator=ind) if not temp_df.empty: temp_df["indicator"] = ind # 添加指标列以便区分 df_list.append(temp_df) if df_list: df = pd.concat(df_list, ignore_index=True) else: df = pd.DataFrame() return _format_dataframe_output(df, output_format)
- src/china_stock_mcp/server.py:694-694 (registration)Registers the 'get_profit_forecast' tool using the @mcp.tool decorator with the specified name and description.@mcp.tool(name="get_profit_forecast", description="获取股票的业绩预测数据，包括预测年报净利润和每股收益")
- Pydantic-based input schema definition using Annotated types and Field descriptions for the tool parameters: symbol (stock code) and output_format.symbol: Annotated[str, Field(description="股票代码 (例如: '600519')")], 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:
- src/china_stock_mcp/server.py:89-117 (helper)Helper function _format_dataframe_output used by the tool to format the resulting DataFrame into the requested output format (json, csv, etc.).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)