Skip to main content
Glama
Sign In
a-share-mcp

a-share-mcp

by shouldnotappearcalm
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_fina_indicator

Query quarterly financial indicators for A-share stocks by code and date range, combining profitability, operation, growth, solvency, cash flow, and DuPont metrics from six sources.

Instructions

    Aggregated financial indicators from 6 Baostock APIs into one convenient query.

    **Data is returned by QUARTER** (Q1, Q2, Q3, Q4) based on financial report dates.
    Input date range determines which quarters to fetch.

    Combines data from:
    - 盈利能力 (Profitability): roeAvg, npMargin, gpMargin, epsTTM
    - 营运能力 (Operation): NRTurnRatio, INVTurnRatio, CATurnRatio
    - 成长能力 (Growth): YOYNI, YOYEquity, YOYAsset
    - 偿债能力 (Solvency): currentRatio, quickRatio, liabilityToAsset
    - 现金流量 (Cash Flow): CFOToOR, CFOToNP, CAToAsset
    - 杜邦分析 (DuPont): dupontROE, dupontAssetTurn, dupontPnitoni

    Output columns include prefixes: profit_*, operation_*, growth_*,
    balance_*, cashflow_*, dupont_* to distinguish data sources.

Input Schema

NameRequiredDescriptionDefault
codeYes
limitNo
formatNomarkdown
end_dateYes
start_dateYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the quarterly aggregation behavior and output column naming conventions, which is valuable. However, it doesn't address important behavioral aspects like rate limits, authentication requirements, data freshness, error conditions, or whether this is a read-only operation (though implied by 'get' naming).

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

Conciseness5/5

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

The description is efficiently structured with clear sections: purpose statement, key behavioral detail (quarterly aggregation), data sources list, and output format explanation. Every sentence adds value with zero wasted words, and it's appropriately front-loaded with the core functionality.

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?

For a tool with 5 parameters, 0% schema coverage, no annotations, and no output schema, the description does a reasonable job explaining the aggregation behavior and output structure. However, it doesn't fully compensate for the missing parameter documentation (especially the 'code' parameter) and lacks details about return format, error handling, or performance characteristics that would be helpful given the complexity.

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?

With 0% schema description coverage for 5 parameters, the description adds significant value by explaining that date range determines which quarters to fetch (clarifying start_date and end_date purpose). However, it doesn't explain the code parameter (stock/company identifier), limit, or format parameters. The description compensates well but doesn't fully cover all parameters.

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 tool aggregates financial indicators from 6 Baostock APIs into one query, specifying the exact data sources (profitability, operation, growth, solvency, cash flow, DuPont analysis). It distinguishes itself from siblings by combining data that appears to be split across multiple specialized tools (e.g., get_profit_data, get_operation_data, get_growth_data, get_dupont_data).

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

Usage Guidelines4/5

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

The description provides clear context for when to use this tool: when needing aggregated financial indicators by quarter, with date ranges determining which quarters to fetch. It implicitly suggests alternatives (using individual specialized tools for specific data types) but doesn't explicitly name them or state when not to use this tool.

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

Deploy Server

Other Tools