Real-time Stock MCP Service

get_valuation_comparison

Retrieve valuation comparison data for a stock by its code. Returns a Markdown table with key metrics for analysis.

Instructions

获取估值比较数据

Args: stock_code: 股票代码，要在数字后加上交易所代码，格式如600000.SH

Returns: 估值比较数据的Markdown表格

Examples: - get_valuation_comparison("600000.SH")

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "stock_code": "<stock_code>"
    },
    "name": "get_valuation_comparison"
  }
}

Input Schema

Name	Required	Description	Default
`stock_code`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.2.1May 17, 2026

TDQS

B3.4/5.0

Behavior2/5

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

No annotations are provided, so the description must fully disclose behavior. It states the return format (Markdown table) but omits details like side effects, data freshness, or authentication needs. As a read operation, basic safety is implied but not explicit.

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 concise, with a clear Args/Returns/Examples structure. It is mostly front-loaded but mixes English and Chinese; the information density is high without being verbose.

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

Completeness4/5

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

Given one simple parameter, the description adequately covers the required input format and output type (Markdown table). The presence of an output schema reduces the need to detail return fields, making it complete for its simplicity.

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?

The input schema has 0% description coverage, but the description adds critical meaning by specifying the stock_code format (e.g., '600000.SH' with exchange suffix). This compensates for the schema's lack of detail.

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

Purpose4/5

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

The description clearly states it retrieves valuation comparison data for a stock, using a specific stock code format. It distinguishes from other tools like get_valuation_analysis primarily by the comparison aspect, but does not explicitly differentiate from siblings.

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?

The description provides a code format requirement for the parameter, implying usage context. However, it offers no guidance on when to choose this tool over alternatives like get_valuation_analysis.

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