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SAS MCP Server

SAS MCP Server

Official
by sassoftware
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Python
Remote

Get Business Rule

get_business_rule
Read-onlyIdempotent

Retrieve a specific rule's definition from a SAS Business Rules rule set using its UUID and parent rule set UUID for targeted inspection.

Instructions

Fetch a single rule's definition from a SAS Business Rules rule set.

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": {
      "ruleset_id": "<ruleset_id>",
      "rule_id": "<rule_id>"
    },
    "name": "get_business_rule"
  }
}

Input Schema

NameRequiredDescriptionDefault
rule_idYesThe rule UUID.
ruleset_idYesThe parent rule set UUID (not its name — list_business_rulesets returns both).

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.7.0
    • changedInput schema / properties / ruleset_id / description
      Previous value: -"The parent rule set UUID."New value: +"The parent rule set UUID (not its name — list_business_rulesets returns both)."
  2. Addedv1.5.0

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description reinforces the read-only nature ('Fetch') but adds no extra behavioral detail such as not-found behavior or version handling, which is acceptable given the annotation coverage.

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?

A single, front-loaded sentence that states the action, target, and scope with no filler or repetition. It is concise yet fully informative.

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?

The tool has only two required string parameters, full parameter descriptions, strong safety annotations, and an output schema. The description provides enough context for an agent to select and invoke the tool correctly; no critical information is missing.

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 coverage is 100%; both parameters have clear descriptions (rule_id is the rule UUID, ruleset_id is the parent ruleset UUID and not its name). The description adds no parameter-level meaning beyond what the schema already provides, so the baseline of 3 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 ('Fetch') and resource ('a single rule's definition') scoped to 'a SAS Business Rules rule set.' This clearly differentiates it from list_business_rules (plural/list) and get_business_ruleset (ruleset-level read).

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 clear context: the tool is for retrieving exactly one rule definition from a ruleset. It doesn't explicitly name alternatives like list_business_rules, but the singular 'rule' wording and the ruleset scope make the intended use case evident without ambiguity.

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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