Skip to main content
Glama

sap_read_table_structure

Retrieve SAP Data Dictionary table metadata, including field names, data types, keys, and descriptions, so developers can understand the schema needed for ABAP analysis, review, and development.

Instructions

Retrieves the metadata of a Data Dictionary table including field definitions, data types, keys, and descriptions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
table_nameYesData Dictionary table name

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed4 schema fields changedv0.1.2
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
    • removedInput schema / additionalProperties
      Removed value: -false
    • changedInput schema / properties / table_name / description
      Previous value: -"SAP table or structure name, e.g. EKKO"New value: +"Data Dictionary table name"
    • addedInput schema / properties / table_name / example
      Added value: +"MARA"
  2. First observedv0.1.0

TDQS

A3.6/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It communicates that the tool retrieves metadata, but it does not explicitly state whether this is read-only, whether special authorizations are required, or any other operational characteristics such as errors or limits.

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 focused sentence with no filler. It front-loads the core purpose and immediately lists the useful contents of the response, making it easy for an agent to understand.

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 metadata retrieval tool without an output schema, the description is reasonably complete: it names the resource and enumerates the key return elements. It does not discuss error cases or permissions, but these are not critical for such a straightforward read operation.

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 schema already fully documents the single parameter, table_name, including its type, example, and description. The tool description adds no extra parameter-level meaning, so the schema coverage 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 states a specific verb ('Retrieves') and resource ('metadata of a Data Dictionary table'), and enumerates the returned content: field definitions, data types, keys, and descriptions. This clearly differentiates it from data-reading siblings like sap_read_table_data by focusing on metadata only.

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 the tool is for inspecting the metadata/structure of a table rather than reading its rows, which provides some usage context. However, it does not explicitly mention alternatives such as sap_get_field_metadata or sap_read_table_data, nor any when-not-to-use guidance.

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

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/NicoHern/abapilot-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server