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SAP Business One Order-to-Cash MCP Server

SAP Business One Order-to-Cash MCP Server

by parmarnaresh86
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

predict_stockout

Identify inventory items at risk of stockout based on current stock and recent daily demand. Provides days of stock remaining and risk levels to prioritize replenishment.

Instructions

Predict which inventory items are at risk of stockout based on current stock and recent daily demand. Returns days-of-stock-remaining per item with risk levels: critical (≤7 days), low (≤30), moderate (≤60), ok.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "predict_stockout"
  }
}

Input Schema

NameRequiredDescriptionDefault
topNNoMax items to return (default 50)
demandDaysNoDays of sales history to derive daily demand (default 90)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior4/5

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 clearly explains what the tool computes and what it returns, including days-of-stock-remaining and the risk-level thresholds. It does not explicitly state that it is read-only, but the 'predict' and 'returns' wording strongly implies a non-mutating analytical operation.

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 a single, information-dense sentence that front-loads the main purpose and immediately follows with the return format and thresholds. Every clause adds value, with no filler or repetition of the tool name.

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?

The description is largely complete for a simple prediction tool: it explains what inputs matter, what the output looks like, and how risk levels are classified. Because there is no output schema, the explicit description of return values is valuable. Still, it does not address when not to use it or how it relates to closely related inventory tools, which leaves a small contextual gap.

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

Parameters3/5

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

The input schema already documents both parameters (topN and demandDays) with 100% coverage, so the baseline applies. The description reinforces the meaning of demandDays through 'recent daily demand' but does not add meaningful new detail beyond the schema, and it does not mention topN at all.

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 identifies the tool's purpose: predicting stockout risk for inventory items based on stock levels and daily demand. It also specifies the exact output format, days-of-stock-remaining per item, with concrete risk thresholds, which distinguishes it from related inventory tools like detect_dead_slow_stock or calc_reorder_point.

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 implies this tool should be used when an agent needs to assess stockout risk using current stock and recent demand. However, it does not explicitly state when to prefer this over sibling tools such as calc_reorder_point, detect_dead_slow_stock, or monitor_reorder_items, so the usage context is clear but the exclusion guidance is missing.

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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