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abap-config-mcp

abap-config-mcp

by netweaver1970
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Describe Database Table

describe_database_table
Read-onlyIdempotent

Shows SAP database table or view field names, types, lengths, descriptions, and key-field markers so you can understand the structure before querying and choose fields to filter or select.

Instructions

Show all field names, types, lengths, and descriptions for a SAP database table or view. Key fields are marked with 🔑. Use this after search_database_tables to understand the structure before querying, so you know which fields to filter or select.

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": {
      "tableName": "<tableName>"
    },
    "name": "describe_database_table"
  }
}

Input Schema

NameRequiredDescriptionDefault
tableNameYesSAP table or view name (e.g. MARA, WLK1, EKKO, Z_MY_TABLE)
connectionIdNoSAP system connection ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.16.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, so the safety profile is covered. The description adds real value by disclosing the return shape (field names, types, lengths, descriptions, and 🔑 key markers), which substitutes for the absent output schema. It does not cover failure behavior for nonexistent tables or how connectionId defaults are resolved.

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 tightly written sentences with no filler. The output content is front-loaded and the workflow guidance follows immediately, matching the order an agent needs it.

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?

With no output schema, the description carries the return-value burden well by enumerating the fields returned. The remaining gap is minor: no note on behavior when the table is missing or on which connection is used if connectionId is omitted.

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%, and the schema already gives the tableName examples (MARA, WLK1, EKKO, Z_MY_TABLE) and connectionId meaning. The description only reaffirms that views are accepted, adding no syntax or lookup guidance beyond the schema. Baseline 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 names a specific verb and resource ("Show all field names, types, lengths, and descriptions for a SAP database table or view") and even specifies a display detail (key fields marked with 🔑). It is clearly distinguishable from search_database_tables, which only finds tables rather than describing them.

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?

It states the exact workflow position — "Use this after search_database_tables" — and the reason for the call: to learn which fields to filter or select before querying. The alternative (read_table_contents) is implicitly ruled out by the ordering advice and the stated goal of understanding structure first.

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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