XTQuantAI
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_trading_datesC | 获取指定市场的交易日期列表 |
| get_stock_listC | 获取指定板块的股票列表 |
| get_instrument_detailC | 获取指定股票的详细信息 |
| get_history_market_dataC | 获取历史行情数据 |
| get_latest_market_dataC | 获取最新行情数据 |
| get_full_market_dataC | 获取历史+最新行情数据 |
| create_chart_panelC | 创建图表面板，显示指定股票的技术指标 |
| create_custom_layoutC | 创建自定义布局，可以指定指标名称、参数名和参数值 |
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 8 tools
Most tools have distinct purposes, but there is notable overlap between get_full_market_data, get_history_market_data, and get_latest_market_data, which could cause confusion about which to use for specific data needs. The other tools target different resources like layouts, stock details, lists, and dates, making them clearer.
All tool names follow a consistent verb_noun pattern using snake_case, such as create_chart_panel, get_full_market_data, and get_instrument_detail. This predictability makes the tool set easy to navigate and understand.
With 8 tools, the count is well-scoped for a financial/quantitative AI server focused on market data, stock analysis, and visualization. Each tool appears to serve a specific function without being excessive or too sparse.
The tool set covers data retrieval, stock analysis, and visualization well, but there are gaps in operations like updating or deleting created layouts/panels, and no tools for executing trades or managing portfolios, which might be expected in a quantitative AI context. This could limit agent workflows.