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MaoBui2907

VNStock MCP Server

by MaoBui2907
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Capabilities

Features and capabilities supported by this server

CapabilityDetails
tools
{
  "listChanged": true
}
logging
{}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
extensions
{
  "io.modelcontextprotocol/ui": {}
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
list_all_icb_industriesB

List all ICB industries from stock market Args: output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

list_all_companies_with_detailsB

List all companies from stock market with details Args: output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_company_overviewC

Get company overview from stock market Args: symbol: str output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_company_newsA

Get company news from stock market Args: symbol: str page_size: int = 10 page: int = 0 output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_company_eventsC

Get company events from stock market Args: symbol: str page_size: int = 10 page: int = 0 output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_company_shareholdersC

Get company shareholders from stock market Args: symbol: str output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_company_officersB

Get company officers from stock market Args: symbol: str filter_by: Literal['working', "all", 'resigned'] = 'working' output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_company_subsidiariesA

Get company subsidiaries from stock market Args: symbol: str filter_by: Literal["all", "subsidiary"] = "all" output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_company_reportsB

Get company reports from stock market Args: symbol: str output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_company_dividendsB

Get company dividends from stock market Args: symbol: str output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_company_insider_dealsB

Get company insider deals from stock market Args: symbol: str output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_company_ratio_summaryC

Get company ratio summary from stock market Args: symbol: str output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_company_trading_statsB

Get company trading stats from stock market Args: symbol: str output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_all_symbol_groupsB

Get all symbol groups from stock market Args: output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_all_symbols_by_groupC

Get all symbols from stock market Args: group: str (group name to get symbols) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_all_symbols_by_industryA

Get all symbols from stock market Args: industry: str = None (if None, return all symbols) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame or json

get_all_symbolsB

Get all symbols from stock market Args: output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame or json

get_all_symbols_detailedB

Get all symbols detailed from stock market Args: output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_income_statementsB

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', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_balance_sheetsC

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', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_cash_flowsA

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', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_finance_ratiosB

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', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_raw_reportB

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', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

list_all_fundsA

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', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

search_fundA

Search fund by name from stock market Args: keyword: str (partial match for fund name to search) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_fund_nav_reportB

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', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_fund_top_holdingA

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', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_fund_industry_holdingB

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', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_fund_asset_holdingB

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', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_gold_priceB

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', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_exchange_rateB

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', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_quote_price_with_indicatorsB

Get quote price with indicators of a symbol from stock market.

Indicators can be specified with or without parameters:

  • Simple: "rsi", "macd", "stochastic"

  • With params: "rsi(window=21)", "macd(fast=12, slow=26, signal=9)"

get_quote_history_priceB

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', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_quote_intraday_priceC

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) page: int = 1 (page number to get intraday price from) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_quote_price_depthA

Get quote price depth from stock market Args: symbol: str (symbol to get price depth) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

get_price_boardB

Get price board from stock market Args: symbols: list[str] (list of symbols to get price board) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription
_list_available_indicatorsList all available indicators. Returns list of dicts with name, description, parameters, output_columns, and usage.
_get_available_indicators_detailedGet list of all available indicators with detailed information. Returns list of dicts with name, description, parameters, output_columns, and usage.

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