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kevynf

AKBridge MCP Server

by kevynf

futures_warehouse_receipt_dce

Read-onlyIdempotent

Retrieve daily warehouse receipt statistics from the Dalian Commodity Exchange for a given trading date, enabling futures inventory and delivery analysis.

Instructions

大连商品交易所-行情数据-统计数据-日统计-仓单日报 http://www.dce.com.cn/dce/channel/list/187.html :param date: 交易日,e.g., "20200702" :type date: str :return: 指定日期的仓单日报数据 :rtype: dict :raises APIError: 大连商品交易所网站启用瑞数反爬虫验证,拒绝程序请求时抛出

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNo20251027

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

B3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is well covered. The description adds useful context that the DCE website uses 瑞数 anti-scraping validation and may raise an APIError if it rejects the request. This is valuable behavioral information not present in annotations, though nothing is said about rate limits or response guarantees.

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 compact and front-loads the resource description before listing the parameter, return, and exception. However, the inclusion of a raw URL and a multi-level Chinese taxonomy string is somewhat redundant and could be streamlined.

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?

The description covers the core purpose, the parameter format, the return type, and a notable failure mode (anti-scraping). However, it lacks any output structure details (no output schema exists) and does not explain the default behavior or when to prefer this tool over similar warehouse receipt tools from other exchanges. It is adequate but incomplete for an agent that needs to decide among many siblings.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It gives the parameter name 'date' and a format example "20200702", which is helpful, but does not explain the default value (20251027) or specify that it is optional and defaults to a specific date. That is a significant omission for a single-parameter tool.

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 states a clear verb+resource: it retrieves the daily warehouse receipt report (仓单日报) from the Dalian Commodity Exchange (大连商品交易所). It even provides the source URL and a full metadata hierarchy. It is not differentiated from siblings like futures_gfex_warehouse_receipt or futures_warehouse_receipt_czce, but the exchange-specific name makes its scope 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?

There is no explicit guidance on when to use this tool versus other warehouse receipt tools (e.g., for GFEX or CZCE) or other DCE data tools. The description implies usage by saying it returns the daily warehouse receipt report, but offers no conditions, prerequisites, or alternatives.

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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