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MCP SAP GUI Server

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sap_set_batch_fields

Fill multiple SAP GUI input fields in one call to populate forms or selection screens quickly. See success counts and the list of fields that failed, simplifying corrections.

Instructions

Fill in multiple input fields at once (dict of field_id to value).

Use this to fill a form or selection screen in one call — more efficient than repeated sap_set_field calls. Table-control cells work too: take the cell_id template of each column from sap_read_table(columns_only=true) and replace {row}.

The result gives counts; results lists only the fields that did NOT succeed (all of them with verbose=true).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsYesDict mapping field_id -> value.
verboseNoList every field in `results`, not only the failures.
validateNoPress Enter after setting fields and return status-bar feedback. Skipped when no fields were actually set.
skip_readonlyNoSilently skip fields whose element reports Changeable == False instead of counting them as failures.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.4.0
    • addedInput schema / properties / verbose
      Added value: +{
+  "default": false,
+  "description": "List every field in `results`, not only the failures.",
+  "type": "boolean"
+}
  2. Changed3 schema fields changedv0.2.2
    • addedInput schema / properties / fields / description
      Added value: +"Dict mapping field_id -> value."
    • addedInput schema / properties / skip_readonly / description
      Added value: +"Silently skip fields whose element reports\nChangeable == False instead of counting them as failures."
    • addedInput schema / properties / validate / description
      Added value: +"Press Enter after setting fields and return status-bar\nfeedback. Skipped when no fields were actually set."
  3. First observedv0.2.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations declare readOnlyHint=false and destructiveHint=false, so the agent knows this mutates but is not destructive. The description adds return-behavior detail (counts, `results` lists failures by default, all with verbose=true) and the table-cell template approach. This adds meaningful context beyond the annotations without contradicting them.

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 short paragraphs with zero filler. The primary purpose is front-loaded, and the efficiency comparison to sap_set_field is stated in the first sentence. Every sentence adds value—no redundancy.

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 tool with 4 parameters and an output schema, the description covers the main use case, return semantics, and the table-cell edge case. It doesn't explain prerequisites or field_id format, but those are likely inferable from the schema and existing patterns. Given the output schema exists, the description is adequately complete for correct invocation.

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%, so the schema already documents all four parameters clearly. The description adds only a minor note about table-control cells and restates the verbose behavior that is already in the schema. It does not compensate with extra detail for any parameter, so 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 clearly states the tool fills multiple input fields at once via a dict, with a specific verb ('fill') and resource ('multiple input fields'). It explicitly contrasts with sap_set_field, so an agent can distinguish it from the single-field sibling.

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 explicitly says 'Use this to fill a form or selection screen in one call — more efficient than repeated sap_set_field calls', naming the alternative and the condition that selects it. It also explains table-control cell usage with a pointer to sap_read_table. This is unambiguous when-to-use guidance.

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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