Skip to main content
Glama
kts982

MCP SAP GUI Server

by kts982

sap_get_column_info

Read-only

Retrieve detailed column metadata from SAP ALV grids or table controls, including names, titles, tooltips, data types, key flags, and cell templates.

Instructions

Get detailed column info from an ALV grid or table control.

Returns column names, titles and tooltips; for an ALV grid also each column's data_type (string, date, decimal, ...) and key flag, for a table control each column's cell_type and cell_id template. For a lighter alternative, use sap_read_table with columns_only=true.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
grid_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. Beyond that, the description discloses behavior that varies by control type: ALV grids yield data_type and key flags, table controls yield cell_type and cell_id templates. It does not cover pagination, cost, or how to obtain a valid grid_id.

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?

Two sentences with the core capability front-loaded and the call-to-action (alternative tool) at the end. The per-control-type detail is packed into one clause rather than padding, so every sentence earns its place.

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?

An output schema exists, so return-value explanation is a bonus rather than a requirement, and annotations cover the safety profile. The description handles both supported control types and the sibling alternative, leaving only the unresolved question of how an agent obtains a valid grid_id.

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 0% for the single grid_id parameter, and the description never explains its format or provenance. The phrase 'ALV grid or table control' only indirectly hints that grid_id identifies such a control, so it does not fully compensate for the coverage gap.

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?

Specific verb ('Get detailed column info') plus resource and explicit scope ('from an ALV grid or table control'). It further distinguishes itself from the sibling sap_read_table by naming the lighter alternative, so an agent can pick between them without opening schemas.

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?

Explicitly routes the agent to a cheaper alternative ('For a lighter alternative, use sap_read_table with columns_only=true'), giving a clear when-to-prefer-other condition. It stops short of stating prerequisites or when this tool is mandatory (e.g., before sap_modify_cell), so it is clear context rather than full when/when-not guidance.

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