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jackdark425

AIGroup Market MCP

by jackdark425

Csi Index Constituents

csi_index_constituents

Retrieve CSI index constituent weights, sector/theme basket quotes, and financial metrics (PE TTM, PB, ROE, dividend yield) for analysis and monitoring.

Instructions

获取中证指数公司(CSI)指数(含行业/主题)的区间行情、成分权重与估值/财务摘要(PE TTM、PB、股息率、ROE、ROA、净利率、每股经营现金流、资产负债率、营收同比、资产周转率、毛利率、三费比率、现金分红率)。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
index_codeYes指数代码(仅限CSI,含行业/主题)。请使用 .SH/.SZ 形式且能在 Tushare index_weight 查询到权重的代码,例如中证证券公司 '399975.SZ';也支持宽基 '000300.SH'、'000905.SH',以及 'sh000300'、'sz399006' 形式
start_dateYes开始日期,YYYYMMDD 或 YYYY-MM-DD
end_dateYes结束日期,YYYYMMDD 或 YYYY-MM-DD
Behavior3/5

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

No annotations are provided, so the description carries the full burden for behavioral disclosure. It describes the data returned (market data, weights, financial metrics) but does not address read-only nature, destructive potential, rate limits, or data freshness. The description is transparent about the output content but lacks behavioral warnings or constraints beyond the stated purpose.

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 sentence that efficiently conveys the tool's purpose and the extensive list of output metrics. While compact, it could benefit from structuring the financial metrics as a bulleted list for readability. No redundant information is present, and the key action verb is front-loaded.

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 the complexity (multiple output metrics per constituent) and absence of an output schema, the description adequately lists the financial metrics but does not explain the output format (e.g., time-series vs. snapshot, per-constituent structure). The tool likely returns a table of constituents with weights and metrics, but this is not clarified. More detail on the data shape and temporal behavior would improve completeness.

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

Parameters4/5

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

Schema coverage is 100% with each parameter described. The description adds value beyond the schema by clarifying that index_code is limited to CSI indices (including industry/theme) and lists accepted formats (e.g., .SH/.SZ, sh000300, sz399006). It also specifies that the tool provides detailed financial metrics, which helps agents understand what the parameters will yield.

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?

Description precisely states the tool retrieves CSI index constituents data including market quotes, weights, and a comprehensive list of financial metrics. It clearly differentiates from sibling tools like stock_data (individual stocks) and index_data (pure index values) by specifying CSI-specific constituents with detailed valuation and financial summaries.

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

Usage Guidelines3/5

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

Description implies use for CSI index constituent data but provides no explicit guidance on when to use this tool versus alternatives (e.g., index_data for broader index information, stock_data for individual stocks). No when-not-to-use or exclusion criteria are stated, leaving the agent to infer usage context from the purpose.

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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