A Share MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_historical_k_dataA | |
| get_stock_basic_infoA | |
| get_dividend_dataC | |
| get_adjust_factor_dataA | |
| get_profit_dataC | Quarterly profitability data. |
| get_operation_dataD | Quarterly operation capability data. |
| get_growth_dataD | Quarterly growth capability data. |
| get_balance_dataC | Quarterly balance sheet data. |
| get_cash_flow_dataD | Quarterly cash flow data. |
| get_dupont_dataC | Quarterly Dupont analysis data. |
| get_performance_express_reportD | Performance express report within date range. |
| get_forecast_reportC | Earnings forecast report within date range. |
| get_fina_indicatorA | |
| get_stock_industryC | Get industry classification for a specific stock or all stocks on a date. |
| get_sz50_stocksC | SZSE 50 constituents. |
| get_hs300_stocksD | CSI 300 constituents. |
| get_zz500_stocksD | CSI 500 constituents. |
| get_index_constituentsC | Generic index constituent fetch (hs300/sz50/zz500). |
| list_industriesC | List distinct industries for a given date. |
| get_industry_membersC | Get all stocks in a given industry on a date. |
| get_trade_datesB | |
| get_all_stockC | |
| search_stocksA | |
| get_suspensionsA | |
| get_deposit_rate_dataD | Benchmark deposit rates. |
| get_loan_rate_dataD | Benchmark loan rates. |
| get_required_reserve_ratio_dataD | Required reserve ratio data. |
| get_money_supply_data_monthC | Monthly money supply data. |
| get_money_supply_data_yearC | Yearly money supply data. |
| get_latest_trading_dateB | Get the latest trading date up to today. |
| get_market_analysis_timeframeC | Return a human-friendly timeframe label. |
| is_trading_dayC | Check if a specific date is a trading day. |
| previous_trading_dayC | Get the previous trading day before the given date. |
| next_trading_dayC | Get the next trading day after the given date. |
| get_last_n_trading_daysC | Return the last N trading dates. |
| get_recent_trading_rangeC | Return a date range string covering the recent N trading days. |
| get_month_end_trading_datesC | Return month-end trading dates for a given year. |
| get_stock_analysisB | |
| normalize_stock_codeC | Normalize a stock code to Baostock format. |
| normalize_index_codeC | Normalize common index codes to Baostock format. |
| list_tool_constantsB | |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 41 tools
Most tools have distinct purposes targeting specific financial data types (e.g., balance sheets, dividends, K-line data), but there is significant overlap in data retrieval patterns. Tools like get_balance_data, get_cash_flow_data, get_profit_data, and get_operation_data all follow the same quarterly data fetch pattern for different metrics, which could cause confusion about which specific financial indicator is needed. However, the clear naming and descriptions help mitigate this overlap.
Tool names follow a highly consistent 'verb_noun' pattern throughout, primarily using 'get_' or 'list_' prefixes (e.g., get_adjust_factor_data, list_industries, search_stocks). Minor deviations like is_trading_day and normalize_stock_code still fit the pattern semantically. This consistency makes the tool set predictable and easy to navigate.
With 41 tools, the count is excessive for a stock data server, leading to bloat and potential overwhelm. Many tools are highly specialized (e.g., get_month_end_trading_dates, get_market_analysis_timeframe) that could be consolidated into broader functions. A more focused set of 15-20 tools would better serve the domain without sacrificing functionality.
The tool set provides comprehensive coverage for Chinese stock market data, including historical prices, financial statements, indices, dividends, trading calendars, and industry classifications. It supports full CRUD-like data retrieval across multiple dimensions (time, frequency, adjustment) and includes utility functions for code normalization and constant listing, leaving no obvious gaps for the stated purpose.