Skip to main content
Glama
Sign In
Kingdee MCP Server

Kingdee MCP Server

by WaHaiLong
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

kingdee_query_production_stock_in

Read-onlyIdempotent

Query production stock-in orders (PRD_Instock) by filters like document status, production order number, or warehouse. Retrieve details including bill number, date, quantity, and material name.

Instructions

查询生产入库单（PRD_Instock）列表。

常用 filter_string：

  • 已审核: "FDocumentStatus='C'"

  • 指定生产订单: "FMoBillNo='MO000001'"

  • 指定仓库: "FStockId.FNumber='CK001'"

推荐 field_keys： FID,FBillNo,FDate,FDocumentStatus,FMoBillNo,FMaterialId.FName,FInQty,FStockId.FName

Returns: str: JSON 格式的生产入库单列表

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": {
      "params": "<params>"
    },
    "name": "kingdee_query_production_stock_in"
  }
}

Input Schema

NameRequiredDescriptionDefault
paramsYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior3/5

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

Annotations already indicate readOnly, non-destructive, idempotent behavior. The description adds minimal behavioral insight beyond return format (JSON) and example filters. No contradiction with annotations.

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 concise, uses bullet points for examples, and clearly states the return type. Every sentence serves a purpose, and the structure is easy to parse.

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

Completeness5/5

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

Given the tool is a simple query with annotations and output schema, the description sufficiently covers purpose, examples, and return format. No additional context needed.

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 descriptions for most parameters (high coverage). The description adds value by providing recommended field_keys and filter examples, which help the agent form correct queries beyond bare schema.

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 queries production stock-in documents (PRD_Instock) and provides specific filter examples and recommended fields, distinguishing it from generic query tools like kingdee_query_bills.

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 gives concrete filter_string and field_keys examples, making usage context clear. However, it does not explicitly state when not to use it or compare to sibling query tools, though the specialization is evident.

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