Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_company_overview | Get company overview from stock market
Args:
symbol: str
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_company_news | Get company news from stock market
Args:
symbol: str
page_size: int = 10
page: int = 0
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_company_events | Get company events from stock market
Args:
symbol: str
page_size: int = 10
page: int = 0
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_company_shareholders | Get company shareholders from stock market
Args:
symbol: str
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_company_officers | Get company officers from stock market
Args:
symbol: str
filter_by: Literal['working', "all", 'resigned'] = 'working'
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_company_subsidiaries | Get company subsidiaries from stock market
Args:
symbol: str
filter_by: Literal["all", "subsidiary"] = "all"
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_company_reports | Get company reports from stock market
Args:
symbol: str
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_company_dividends | Get company dividends from stock market
Args:
symbol: str
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_company_insider_deals | Get company insider deals from stock market
Args:
symbol: str
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_company_ratio_summary | Get company ratio summary from stock market
Args:
symbol: str
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_company_trading_stats | Get company trading stats from stock market
Args:
symbol: str
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_all_symbol_groups | Get all symbol groups from stock market
Args:
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_all_industries | Get all symbols from stock market
Args:
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame or json |
| get_all_symbols_by_group | Get all symbols from stock market
Args:
group: str (group name to get symbols)
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_all_symbols_by_industry | Get all symbols from stock market
Args:
industry: str = None (if None, return all symbols)
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame or json |
| get_all_symbols | Get all symbols from stock market
Args:
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame or json |
| get_income_statements | Get income statements of a company from stock market
Args:
symbol: str (symbol of the company to get income statements)
period: Literal['quarter', 'year'] = 'year' (period to get income statements)
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_balance_sheets | Get balance sheets of a company from stock market
Args:
symbol: str (symbol of the company to get balance sheets)
period: Literal['quarter', 'year'] = 'year' (period to get balance sheets)
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_cash_flows | Get cash flows of a company from stock market
Args:
symbol: str (symbol of the company to get cash flows)
period: Literal['quarter', 'year'] = 'year' (period to get cash flows)
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_finance_ratios | Get finance ratios of a company from stock market
Args:
symbol: str (symbol of the company to get finance ratios)
period: Literal['quarter', 'year'] = 'year' (period to get finance ratios)
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_raw_report | Get raw report of a company from stock market
Args:
symbol: str (symbol of the company to get raw report)
period: Literal['quarter', 'year'] = 'year' (period to get raw report)
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| list_all_funds | List all funds from stock market
Args:
fund_type: Literal['BALANCED', 'BOND', 'STOCK', None ] = None (if None, return funds in all types)
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| search_fund | Search fund by name from stock market
Args:
keyword: str (partial match for fund name to search)
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_fund_nav_report | Get nav report of a fund from stock market
Args:
symbol: str (symbol of the fund to get nav report)
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_fund_top_holding | Get top holding of a fund from stock market
Args:
symbol: str (symbol of the fund to get top holding)
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_fund_industry_holding | Get industry holding of a fund from stock market
Args:
symbol: str (symbol of the fund to get industry holding)
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_fund_asset_holding | Get asset holding of a fund from stock market
Args:
symbol: str (symbol of the fund to get asset holding)
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_gold_price | Get gold price from stock market
Args:
date: str = None (if None, return today's price. Format: YYYY-MM-DD)
source: Literal['SJC', 'BTMC'] = 'SJC' (source to get gold price)
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_exchange_rate | Get exchange rate of all currency pairs from stock market
Args:
date: str = None (if None, return today's price. Format: YYYY-MM-DD)
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_quote_history_price | Get quote price history of a symbol from stock market
Args:
symbol: str (symbol to get history price)
start_date: str (format: YYYY-MM-DD)
end_date: str = None (end date to get history price. None means today)
interval: Literal['1m', '5m', '15m', '30m', '1H', '1D', '1W', '1M'] = '1D' (interval to get history price)
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_quote_intraday_price | Get quote intraday price from stock market
Args:
symbol: str (symbol to get intraday price)
page_size: int = 500 (max: 100000) (number of rows to return)
last_time: str = None (last time to get intraday price from)
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_quote_price_depth | Get quote price depth from stock market
Args:
symbol: str (symbol to get price depth)
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
| get_price_board | Get price board from stock market
Args:
symbols: list[str] (list of symbols to get price board)
output_format: Literal['json', 'dataframe'] = 'json'
Returns:
pd.DataFrame |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |