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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

segment_customers_rfm

Score customers 1-5 on recency, frequency, and monetary value; classify them as Champions, At Risk, Lost, or other segments. Use these RFM groups to target retention and growth.

Instructions

RFM (Recency, Frequency, Monetary) customer segmentation. Scores each customer 1-5 on how recently they bought, how often, and how much — then classifies them as Champions, Loyal, At Risk, Cannot Lose Them, New Customers, Potential Loyalists, Needs Attention, or Lost.

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": "segment_customers_rfm"
  }
}

Input Schema

NameRequiredDescriptionDefault
lookbackDaysNoHistory window in days (default 365, max 730)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.8/5.0
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 that customers are scored 1-5 on recency, frequency, and monetary value, and then classified into named segments. It doesn't mention side effects, but this is clearly an analytical, read-only operation and the scoring behavior is well disclosed.

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 consists of one tight sentence that front-loads the tool's purpose ('RFM customer segmentation') and then packs in highly specific details: the 1-5 scoring scale, the RFM dimensions, and the full list of segment classifications. There is no filler or redundancy.

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?

For a simple one-parameter analytical tool with no output schema, the description is largely complete. It explains the methodology, scoring scale, and result categories. The main gap is that it doesn't describe the exact return structure or how lookbackDays influences the segmentation, but the schema covers the parameter and the core behavior is clear.

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 single parameter lookbackDays is fully described in the input schema with its default and maximum values, so schema coverage is 100%. The tool description adds no additional parameter-level detail beyond the schema, which is covered by the baseline score of 3.

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 the tool's purpose: RFM-based customer segmentation, with a specific verb ('scores') and resource ('customers'), plus the scoring scale and segment names. It is distinguishable from siblings by its RFM focus, but it does not explicitly name or contrast any alternative 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 the tool: when RFM segmentation is needed. However, it gives no explicit guidance on when to choose this over similar analytics siblings like detect_customer_churn, calc_customer_clv, or analyze_abc_xyz, and it mentions no exclusions 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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