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A-Share MCP Server

MIT License
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market_overview.py7.11 kB
""" Market overview tools for the MCP server. Includes trading calendar, stock list, and discovery helpers. """ import logging from typing import Optional from mcp.server.fastmcp import FastMCP from src.data_source_interface import FinancialDataSource, NoDataFoundError, LoginError, DataSourceError from src.formatting.markdown_formatter import format_df_to_markdown, format_table_output logger = logging.getLogger(__name__) def register_market_overview_tools(app: FastMCP, active_data_source: FinancialDataSource): """ Register market overview tools with the MCP app. Args: app: The FastMCP app instance active_data_source: The active financial data source """ @app.tool() def get_trade_dates(start_date: Optional[str] = None, end_date: Optional[str] = None, limit: int = 250, format: str = "markdown") -> str: """ Fetch trading dates within a specified range. Args: start_date: Optional. Start date in 'YYYY-MM-DD' format. Defaults to 2015-01-01 if None. end_date: Optional. End date in 'YYYY-MM-DD' format. Defaults to the current date if None. Returns: Markdown table with 'is_trading_day' (1=trading, 0=non-trading). """ logger.info( f"Tool 'get_trade_dates' called for range {start_date or 'default'} to {end_date or 'default'}") try: # Add date validation if desired df = active_data_source.get_trade_dates( start_date=start_date, end_date=end_date) logger.info("Successfully retrieved trade dates.") meta = {"start_date": start_date or "default", "end_date": end_date or "default"} return format_table_output(df, format=format, max_rows=limit, meta=meta) except NoDataFoundError as e: logger.warning(f"NoDataFoundError: {e}") return f"Error: {e}" except LoginError as e: logger.error(f"LoginError: {e}") return f"Error: Could not connect to data source. {e}" except DataSourceError as e: logger.error(f"DataSourceError: {e}") return f"Error: An error occurred while fetching data. {e}" except ValueError as e: logger.warning(f"ValueError: {e}") return f"Error: Invalid input parameter. {e}" except Exception as e: logger.exception( f"Unexpected Exception processing get_trade_dates: {e}") return f"Error: An unexpected error occurred: {e}" @app.tool() def get_all_stock(date: Optional[str] = None, limit: int = 250, format: str = "markdown") -> str: """ Fetch a list of all stocks (A-shares and indices) and their trading status for a date. Args: date: Optional. The date in 'YYYY-MM-DD' format. If None, uses the current date. Returns: Markdown table listing stock codes and trading status (1=trading, 0=suspended). """ logger.info( f"Tool 'get_all_stock' called for date={date or 'default'}") try: # Add date validation if desired df = active_data_source.get_all_stock(date=date) logger.info( f"Successfully retrieved stock list for {date or 'default'}.") meta = {"as_of": date or "default"} return format_table_output(df, format=format, max_rows=limit, meta=meta) except NoDataFoundError as e: logger.warning(f"NoDataFoundError: {e}") return f"Error: {e}" except LoginError as e: logger.error(f"LoginError: {e}") return f"Error: Could not connect to data source. {e}" except DataSourceError as e: logger.error(f"DataSourceError: {e}") return f"Error: An error occurred while fetching data. {e}" except ValueError as e: logger.warning(f"ValueError: {e}") return f"Error: Invalid input parameter. {e}" except Exception as e: logger.exception( f"Unexpected Exception processing get_all_stock: {e}") return f"Error: An unexpected error occurred: {e}" @app.tool() def search_stocks(keyword: str, date: Optional[str] = None, limit: int = 50, format: str = "markdown") -> str: """ Search stocks by code substring on a date. Args: keyword: Substring to match in the stock code (e.g., '600', '000001'). date: Optional 'YYYY-MM-DD'. If None, uses current date. limit: Max rows to return. Defaults to 50. format: Output format: 'markdown' | 'json' | 'csv'. Defaults to 'markdown'. Returns: Matching stock codes with their trading status. """ logger.info("Tool 'search_stocks' called keyword=%s, date=%s, limit=%s, format=%s", keyword, date or "default", limit, format) try: if not keyword or not keyword.strip(): return "Error: 'keyword' is required (substring of code)." df = active_data_source.get_all_stock(date=date) if df is None or df.empty: return "(No data available to display)" kw = keyword.strip().lower() # baostock returns 'code' like 'sh.600000' filtered = df[df["code"].str.lower().str.contains(kw, na=False)] meta = {"keyword": keyword, "as_of": date or "current"} return format_table_output(filtered, format=format, max_rows=limit, meta=meta) except Exception as e: logger.exception("Exception processing search_stocks: %s", e) return f"Error: An unexpected error occurred: {e}" @app.tool() def get_suspensions(date: Optional[str] = None, limit: int = 250, format: str = "markdown") -> str: """ List suspended stocks for a date. Args: date: Optional 'YYYY-MM-DD'. If None, uses current date. limit: Max rows to return. Defaults to 250. format: Output format: 'markdown' | 'json' | 'csv'. Defaults to 'markdown'. Returns: Table of stocks where tradeStatus==0. """ logger.info("Tool 'get_suspensions' called date=%s, limit=%s, format=%s", date or "current", limit, format) try: df = active_data_source.get_all_stock(date=date) if df is None or df.empty: return "(No data available to display)" # tradeStatus: '1' trading, '0' suspended if "tradeStatus" not in df.columns: return "Error: 'tradeStatus' column not present in data source response." suspended = df[df["tradeStatus"] == '0'] meta = {"as_of": date or "current", "total_suspended": int(suspended.shape[0])} return format_table_output(suspended, format=format, max_rows=limit, meta=meta) except Exception as e: logger.exception("Exception processing get_suspensions: %s", e) return f"Error: An unexpected error occurred: {e}"

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