SAP Business One Order-to-Cash MCP Server

analyze_vendor_lead_time

Evaluate vendor lead time reliability from purchase order history. Get average lead days, variability, and a reliability rating to identify dependable suppliers.

Instructions

Analyse vendor lead time reliability using purchase order data (PO creation date → due date). Returns average lead days, standard deviation, min/max per vendor, and a reliability rating (high/medium/low based on std dev).

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": "analyze_vendor_lead_time"
  }
}

Input Schema

Name	Required	Description	Default
`months`	No	Months of PO history to analyse (default 6, max 24)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Aug 26, 2026

TDQS

A4.1/5.0

Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the data source, the calculation basis (creation to due date), the output metrics, and the reliability rating logic based on std dev. It does not explicitly state it is read-only, but the 'Analyse' verb and return-value framing strongly imply a non-mutating 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 efficient sentence with zero filler. It front-loads the purpose, clarifies the data source in parentheses, and then lists the outputs and rating rule without redundancy.

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?

Despite having no output schema, the description fully explains the return values (average lead days, std dev, min/max per vendor, reliability rating). Combined with the fully documented parameter schema and the low complexity of the tool, an agent has everything needed to invoke it correctly.

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?

Schema description coverage is 100% for the only parameter (months, default 6, max 24). The description itself adds no parameter-specific semantics, so the baseline score applies.

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 uses a specific verb ('Analyse') and a clear resource ('vendor lead time reliability') backed by a specific data source (PO creation date → due date). It also enumerates the exact return metrics, making the tool's purpose unmistakable and distinct from sibling analytics tools.

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 when to use this tool—when vendor lead time reliability is needed—but gives no explicit guidance on when not to use it or how it differs from related siblings like analyze_on_time_delivery. Context is present but no alternatives or exclusions are stated.

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

Deploy Server