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Check ABAP released-API status

check_released_api
Read-onlyIdempotent

Look up ABAP objects in SAP's Cloudification list to see if each is a released API for ABAP Cloud, deprecated, or not released, with CDS successor hints for classic tables.

Instructions

Look up ABAP repository objects (DB tables, CDS view entities, function modules, classes, interfaces, …) in SAP's published ABAP Cloudification list and report, per object, whether it is a 'released' API (safe to use in ABAP Cloud / Clean Core), 'deprecated' (released but being retired), or 'not-released' (a classic/internal object that is not a public API — e.g. most classic DDIC tables) — with a curated CDS successor hint for common tables. This reflects SAP's official Cloudification list as bundled in this package (snapshot 2026-08-24); it ships offline with the server. Use this when you need to know if your code may reference a given object in ABAP Cloud, or which released CDS view to use instead of a classic table. This explicit lookup complements check_cloud_readiness's limited, source-extracted released-API observations and can check objects that do not appear in the supplied source. It does not connect to any SAP system, does not run ATC, and is only as current as the bundled snapshot — a system's own released-API list (ATC check API_RELEASE_STATE_CHECK / SAP_CP_READINESS) remains authoritative; treat an 'absent from the list' result as 'not-released as of the snapshot', not as proof. Example: check_released_api({ "objects": ["MARA", "I_Product", "BAPI_MATERIAL_GET_DETAIL"] }).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
objectsYesObjects to check, 1–200 per call. Each is a bare name string or a { name, type? } object, e.g. ["MARA", { "name": "I_Product", "type": "CDS_STOB" }].

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceYesURL of the SAP Apache-2.0 source the snapshot was built from.
resultsYes
snapshotDateYesDate of the bundled SAP Cloudification snapshot these results reflect.

Schema Changelog

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

  1. First observedv0.4.5

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already indicate read-only and idempotent behavior, and the description adds meaningful context beyond that: the tool ships offline, uses a specific snapshot date (2026-08-24), does not connect to any SAP backend, and does not modify any system or source file. This gives the agent an accurate safety and freshness profile.

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 dense but well organized: it front-loads the object types and result categories, then provides the offline/snapshot constraint, the use case, and the sibling distinction. Every sentence conveys a distinct, necessary fact with no filler.

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?

For a lookup tool with one input and a known set of output statuses, the description is complete: it covers accepted object types, result categories, CDS successor hints, data source/snapshot, offline behavior, non-mutating behavior, and the relationship to check_cloud_readiness. The output schema handles detailed return structure, so the description does not need to duplicate it.

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 single parameter 'objects' is already fully described in the input schema, including the 1–200 limit, bare string vs object forms, examples, and optional disambiguation types. The description adds no additional parameter-level syntax or format details, so the schema carries the heavy lifting.

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: "Look up ABAP repository objects ... in SAP's published ABAP Cloudification list" and reports per-object status ('released', 'deprecated', 'not-released') plus a CDS successor hint. It also differentiates itself from the sibling check_cloud_readiness, so an agent can tell them apart.

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?

It gives a clear when-to-use: "when you need to know if your code may reference a given object in ABAP Cloud, or which released CDS view to use instead of a classic table." It also names the relevant alternative, check_cloud_readiness, and explains how this tool complements it, though it does not explicitly state when not to use the tool.

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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