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xinkuang

China Stock MCP

by xinkuang

get_stock_volatility

Calculate stock volatility metrics from minute-level historical prices over a customizable date range, supporting different periods and adjustment types.

Instructions

通过分钟级历史行情计算指定个股的波动率指标

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYes股票代码 (例如: '000001')
start_dateYes开始日期,格式为 YYYY-MM-DD HH:MM:SS (例如: '2021-10-20 09:30:00')
end_dateYes结束日期,格式为 YYYY-MM-DD HH:MM:SS (例如: '2024-11-01 15:00:00')
periodYes分钟级历史行情时间周期,分钟级别 (例如: '1', '5', '15', '30', '60')
adjustNo复权类型: none, qfq(前复权), hfq(后复权)。默认:nonenone
output_formatNo输出数据格式: json, csv, xml, excel, markdown, html。默认: markdownmarkdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden but only states it uses minute-level history to calculate volatility. It does not disclose output structure, read-only nature, rate limits, or potential side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence with no wasted words. However, it could benefit from a slight expansion to include output details without becoming verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that an output schema exists, the description does not need to explain return values, but it is incomplete regarding the specific volatility metrics computed. Adequate but lacks context on what the agent will receive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The tool description adds no extra parameter meaning beyond the parameter descriptions themselves.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb (calculate) and resource (volatility indicators for specified stocks), distinguishing it from sibling tools that handle financial statements, indices, or news. It is specific and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives. It does not mention prerequisites, exclusions, or scenarios where other tools (e.g., get_hist_data) might be preferred.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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