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SAS MCP Server

SAS MCP Server

Official
by sassoftware
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Python
Remote

List Compute Tables

list_compute_tables
Read-onlyIdempotent

List tables in a SAS library within a compute context, including WORK or assigned librefs. View available SAS/Compute tables to plan your next code steps.

Instructions

List the tables in a SAS library within a compute context.

These are SAS/Compute tables (e.g. WORK or an assigned libref), distinct from in-memory CAS tables (see list_castables). Runs in the reusable per-user compute session for the context.

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": {
      "compute_context_name": "<compute_context_name>",
      "library_name": "<library_name>"
    },
    "name": "list_compute_tables"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum number of tables to return (default 50).
startNoOffset of the first table to return (default 0).
filter_nameNoOptional name filter (substring match).
library_nameYesName of the SAS library/libref (e.g. 'WORK', 'SASHELP').
compute_context_nameYesName of the compute context (see list_compute_contexts).

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.2.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context beyond the annotations by explaining that the tool runs in the reusable per-user compute session, which is important for agents to understand session-dependent behavior.

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 compact and efficient. The first sentence immediately states the action, and the second paragraph adds the key distinction and execution context without any filler or repetition of schema details.

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 strong annotations, a fully documented input schema, and an output schema, so the description does not need to explain return values. It covers the key operational context, including the compute session behavior and how this tool differs from CAS table listing, making it complete for an agent to select and invoke 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%, with each parameter including a meaningful description such as library example 'WORK'/'SASHELP' and the compute context reference. The description reinforces the meaning of library_name and compute_context_name but does not substantially add parameter-level detail beyond the schema, so a baseline score of 3 is appropriate.

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 states a specific verb and resource: listing tables in a SAS library within a compute context. It explicitly differentiates SAS/Compute tables from in-memory CAS tables and points to list_castables as the sibling for that case, making it easy for an agent to distinguish this tool from similar ones.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear usage context by stating that this tool handles SAS/Compute tables, not CAS tables, and explicitly references list_castables as the alternative for CAS tables. It also clarifies that the operation runs in the reusable per-user compute session, which tells the agent when this tool is appropriate.

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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