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liqiongyu

Xueqiu MCP

by liqiongyu

balance

Retrieve balance sheet data for specific stocks to analyze financial health. Specify stock codes and parameters to access structured financial information from the Xueqiu MCP server.

Instructions

获取资产负债表数据

Args: stock_code: 股票代码 is_annals: 只获取年报,默认为1 count: 返回数据数量,默认5条

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stock_codeNoSZ000002
is_annalsNo
countNo

Implementation Reference

  • main.py:167-177 (handler)
    The handler function for the 'balance' MCP tool. It is decorated with @mcp.tool() for registration, fetches asset balance sheet data from pysnowball library, processes timestamps, and returns the data as dict.
    @mcp.tool() def balance(stock_code: str="SZ000002", is_annals: int = 1, count: int = 5) -> dict: """获取资产负债表数据 Args: stock_code: 股票代码 is_annals: 只获取年报,默认为1 count: 返回数据数量,默认5条 """ result = ball.balance(symbol=stock_code, is_annals=is_annals, count=count) return process_data(result)
  • main.py:34-62 (helper)
    Shared helper function used by the balance tool (and others) to process the raw data, primarily converting timestamps to readable datetime strings.
    def process_data(data, process_config=None): """ 通用数据处理函数,可扩展添加各种数据处理操作 Args: data: 原始数据 process_config: 处理配置字典,用于指定要执行的处理操作 例如: {'convert_timestamps': True, 'other_process': params} Returns: 处理后的数据 """ if process_config is None: # 默认配置 process_config = { 'convert_timestamps': True } # 如果开启了时间戳转换 if process_config.get('convert_timestamps', True): data = convert_timestamps(data) # 在这里可以添加更多的数据处理逻辑 # 例如: # if 'format_numbers' in process_config: # data = format_numbers(data, **process_config['format_numbers']) return data
  • main.py:14-31 (helper)
    Supporting helper recursively called by process_data to convert timestamp fields in the data to formatted datetime strings.
    def convert_timestamps(data): """递归地将数据中的所有 timestamp 转换为 datetime 字符串""" if isinstance(data, dict): for key, value in list(data.items()): if key == 'timestamp' and isinstance(value, (int, float)) and value > 1000000000000: # 毫秒级时间戳 data[key] = datetime.datetime.fromtimestamp(value/1000).strftime('%Y-%m-%d %H:%M:%S') elif key == 'timestamp' and isinstance(value, (int, float)) and value > 1000000000: # 秒级时间戳 data[key] = datetime.datetime.fromtimestamp(value).strftime('%Y-%m-%d %H:%M:%S') elif key.endswith('_date') and isinstance(value, (int, float)) and value > 1000000000000: # 毫秒级时间戳 data[key] = datetime.datetime.fromtimestamp(value/1000).strftime('%Y-%m-%d %H:%M:%S') elif key.endswith('_date') and isinstance(value, (int, float)) and value > 1000000000: # 秒级时间戳 data[key] = datetime.datetime.fromtimestamp(value).strftime('%Y-%m-%d %H:%M:%S') elif isinstance(value, (dict, list)): data[key] = convert_timestamps(value) elif isinstance(data, list): for i, item in enumerate(data): data[i] = convert_timestamps(item) return data

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