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Configure an MCP Server Created from an HTTP EndpointConfigure an MCP Server Created from an HTTP EndpointDocuments configuring API Management’s HTTP-source MCP server tools, resources, prompts and policies. Resources are selected from GET operations and have URI templates/content types; prompts define User/Assistant messages with optional arguments, alongside MCP policy configuration.
MCP Server — SAP Integration SuiteMCP Server — SAP Integration SuiteSAP's own page for the MCP Server artifact in SAP Integration Suite, and where the gateway that runs it is described: MCP clients and API clients reach the same backends through two gateways that share security, traffic management and multi-protocol connectivity. Sets out the three primitives a server may expose — tools derived from API operations with an input and output schema, resources addressed by URI for context rather than action, and prompts as reusable interaction patterns. Says availability depends on the Integration Suite service plan, and points at the three creation paths as separate pages.
Model Context Protocol (MCP)Model Context Protocol (MCP)Frames the Model Context Protocol as the answer to an M-times-N integration problem: one shared protocol turns M agents and N tools into M plus N connections, and one server can be called by any compliant agent. On SAP BTP its implementation section lists an SAP MCP Hub as a no-code way to expose enterprise tools, SAP Integration Suite's MCP Gateway as what it calls the governed path for exposing SAP and non-SAP APIs as MCP-compliant tools, custom SDK-based servers, SAP's MCP servers for development, and an MCP adapter for CDS as a CAP plugin marked coming soon. That is the ground MCP servers covers; for security it points at a separate page.
RAP - Native File UploadRAP - Native File UploadA workaround for uploading a file into a RAP application ahead of SAP's own upload and download solution, which is still pending: two abstract root entities — one holding the file's bytes, MIME type and filename, one for a popup dialog — joined by an association flagged with hierarchy, exposed through a static action declared with DEEP PARAMETER so the nested structure reaches the handler. The trade-offs are stated plainly: the popup takes no default values, only one file uploads at a time, and the UI annotation on the attachment field is ignored because its label is read from the sub-entity's own name.Björn S., published 2026-08-18
052: 10 Minutes from Start to Launchpad052: 10 Minutes from Start to LaunchpadWalks a RAP application from a root CDS view entity through a consumption projection and its associations to a metadata extension: a facet per field group, a hidden field via UI.hidden, and a selection field on the ABAP package, all in a Customer-layer DDLX source read by the generated Fiori elements app. It then covers the parts ABAP CDS modelling and annotation stop short of — service definition and binding, generating the UI in Business Application Studio, and wiring the deployed app into the Fiori Launchpad through an IAM App and business catalog.Björn S., published 2026-09-07
ABAP in Practice - Creating a Setup AppABAP in Practice - Creating a Setup AppWalks through an unmanaged custom entity behind a static Fiori Elements setup app: a factory maps step IDs to implementation classes behind one interface, and the transactional model sets every CRUD operation internal while adding CheckStep and ExecuteStep actions instead of generated persistence. It buffers the executed step for the save sequence and moves an API that issues a COMMIT to a background process via bgPF, since a COMMIT inside the action is forbidden in strict mode.Björn S., published 2026-08-28
RAP - Singleton PatternRAP - Singleton PatternBuilds the RAP Singleton pattern: a root CDS view entity constrained to always return exactly one row, its composition child for line items, and a transactional model behaviour definition — managed with unmanaged save, a determination that fills the user ID, and an EML update inside SAVE_MODIFIED to write the saved data elsewhere. Generates the Fiori elements object-page app from that service and adjusts Component.js so preferredMode lands the user in edit mode against the fixed semantic key, since the app always has exactly one record to open.Björn S., published 2026-08-25
Content-based Agents with SAP Joule Studio Agent BuilderContent-based Agents with SAP Joule Studio Agent BuilderJoule Studio, classic edition, the capability in SAP Build the page calls Joule Studio, is where an organisation creates and manages its own Joule skills and Joule agents; its Agent Builder is for a custom agent that handles a multi-step task by combining instructions, model-backed planning and reasoning, and a configured set of tools, Joule skills, document resources, MCP servers, or other agents run as subagents. The page states an agent executes inside the calling user's own security context through SAP Cloud Identity Services, and can be tried against a test conversation before deployment. That is the tool-and-turn-taking ground agent tooling covers, here built through Joule Studio rather than in application code.
Custom Joule SkillsCustom Joule SkillsA custom Joule skill is a workflow written to extend what Joule does out of the box for one specific business need, built and deployed through Joule Studio in SAP Build; the page states this is the supported way to extend Joule's built-in capabilities. Through Joule Studio a skill reaches SAP and external APIs via the destinations already configured in the BTP subaccount and Build environment, with the workflow itself versioned, monitored and deployable from the same tool.
Pro-Code AI AgentsPro-Code AI AgentsPro-code agents are the most flexible way the page frames building an agentic workflow on SAP BTP: full autonomy, custom API integrations and algorithms chosen by the developer, set against declarative alternatives such as content-based agents and Joule Scenarios. It names LangGraph as the framework it recommends for production, enterprise-grade agentic workflows, alongside the ReAct pattern as the plan-act-observe loop such an agent runs. That is the ground agent tooling covers, building an agent's own tool-calling loop rather than exposing an application to somebody else's agent.
Content FilteringContent FilteringContent filtering screens a large language model's input and output for low-quality, irrelevant or unsafe content: the four categories it names being hateful, violent, sexual and vulgar content, checking a request once on the way in and once on the way back. The page states smaller models can do this filtering efficiently, reading perplexity scores to flag anomalies, with the aim that SAP AI Core produces content meeting a stated safety standard, which is the ground content filtering covers on the BTP door.
Data MaskingData MaskingData masking replaces identifiable or confidential text in a prompt with placeholders such as <Person_0> or <Organization_1> before it reaches a large language model, using pattern matching and machine learning to find what to replace. The page states SAP AI Core supports it as a feature and sets out five steps for applying it, defining the masking scope, choosing a technique, preserving the prompt's intent, checking compliance and risk, then testing and monitoring the result. That is the shape data masking takes on the BTP door.
Access to Generative AI ModelsAccess to Generative AI ModelsSets out the plain way to call a deployed generative AI model on SAP BTP: a request that carries the prompt, the model and the parameters that control generation, with the same code able to switch between models. It lists data masking, prompt templating and filtering as features that come with the access rather than as code the caller writes, which is the shape LLM integration takes on the BTP door; the page's implementation sections sit behind its steps and were not read.
Content FilteringContent FilteringContent filtering screens a large language model's input and output for low-quality, irrelevant or unsafe content: the four categories it names being hateful, violent, sexual and vulgar content, checking a request once on the way in and once on the way back. The page states smaller models can do this filtering efficiently, reading perplexity scores to flag anomalies, with the aim that SAP AI Core produces content meeting a stated safety standard, which is the ground content filtering covers on the BTP door.
Data MaskingData MaskingData masking replaces identifiable or confidential text in a prompt with placeholders such as <Person_0> or <Organization_1> before it reaches a large language model, using pattern matching and machine learning to find what to replace. The page states SAP AI Core supports it as a feature and sets out five steps for applying it, defining the masking scope, choosing a technique, preserving the prompt's intent, checking compliance and risk, then testing and monitoring the result. That is the shape data masking takes on the BTP door.
Document GroundingDocument GroundingDocument Grounding is a managed retrieval-augmented-generation service under the Generative AI Hub on BTP, which SAP's page on SAP AI Core places inside that service: it ingests documents from Amazon S3, SharePoint, SAP Document Management Service, SAP Work Zone or an SFTP server, and handles chunking, embedding and retrieval itself, refreshing content automatically when a source document changes. The page states this managed path is recommended for most enterprise scenarios because it covers the whole lifecycle end to end, and offers a separate Document Grounding Vector API for data that is already chunked and embedded, for cases that need finer control over chunking and metadata.
Prompt TemplatingPrompt TemplatingPrompt templating replaces a static prompt with a structured, reusable template whose placeholders are filled in at runtime, which the page says helps LLM responses stay consistent and lets the same instructions be adapted across tasks. On SAP AI Core this is implemented through the Prompt Registry, and the page states that storing prompts as plain strings in code is possible but not recommended. That is prompt management as a stored and managed object rather than a string embedded in the caller.
Prompt TemplatingPrompt TemplatingPrompt templating replaces a static prompt with a structured, reusable template whose placeholders are filled in at runtime, which the page says helps LLM responses stay consistent and lets the same instructions be adapted across tasks. On SAP AI Core this is implemented through the Prompt Registry, and the page states that storing prompts as plain strings in code is possible but not recommended. That is prompt management as a stored and managed object rather than a string embedded in the caller.
Document GroundingDocument GroundingDocument Grounding is a managed retrieval-augmented-generation service under the Generative AI Hub on BTP, which SAP's page on SAP AI Core places inside that service: it ingests documents from Amazon S3, SharePoint, SAP Document Management Service, SAP Work Zone or an SFTP server, and handles chunking, embedding and retrieval itself, refreshing content automatically when a source document changes. The page states this managed path is recommended for most enterprise scenarios because it covers the whole lifecycle end to end, and offers a separate Document Grounding Vector API for data that is already chunked and embedded, for cases that need finer control over chunking and metadata.
Vector RAG vs Graph RAGVector RAG vs Graph RAGA section introduction rather than the comparison itself: it states that the choice between Vector RAG and Graph RAG depends on the domain and the task, and that Vector RAG is the one to use when the subject area has a clear description and the model must be held to specific data structures and attribute values. The four sub-pages it introduces, two on vector-based and two on graph-based RAG, carry the comparison. It sits on the same retrieval question retrieval-augmented generation answers, without naming CDS, CAP or a store.
Agentic AI Security & GovernanceAgentic AI Security & GovernanceNames seven threat categories agentic AI introduces beyond ordinary application security: prompt injection, excessive agency, supply-chain and model-integrity compromise, memory poisoning, improper output handling, resource abuse and agent-to-agent communication poisoning. Its answer is a defence-in-depth structure of security controls, input validation, privilege management, supply-chain checks, memory segmentation, output validation, execution quotas, secure communication, paired with governance and oversight: audit logging, explainability, human-in-the-loop review, fairness assessment and continuous monitoring. States the reason plainly: an agent decides, chains actions across turns, keeps memory between them and can act on real systems, a different risk profile from a single request-response call. That is the authorisation and audit-trail question tool governance is named for.
BTP - Authorization ObjectBTP - Authorization ObjectWalks through building a classic ABAP authorization object for the ABAP environment — an authorization field, the object itself created in ABAP Development Tools rather than the classic SU21 transaction, and its activities (01 create, 02 change, 03 display, and others) — then wires it into a CDS role's access control with the pfcg_auth aspect on the WHERE condition, which is authorization's ABAP form: CDS access control limiting what a view entity returns to the conditions in a CDS role. The check inherits down to a consumption view and even the Data Preview, and the piece notes the WITH PRIVILEGED ACCESS addition developers use in the SQL console to bypass it while testing.Björn S., published 2026-08-07
BTP - Restriction TypeBTP - Restriction TypeWalks through creating a Restriction Type and Restriction Field for an ABAP RAP authorization object, so the values an IAM app would otherwise fix as static entries can instead be maintained per Business Role in the Fiori Launchpad. Read and Write access on the restriction still follow the activities defined on the authorization object itself (03 for read, 01/02/06 for write), and the piece shows the effect end to end: a Fiori app narrowed to only the business partners assigned on the role. This is the ABAP door's authorization mechanism made dynamic — an access decision moved from the IAM app's fixed values onto the role, without touching the underlying CDS access control.Björn S., published 2026-08-11
RAP - Feature Control (Part 2)RAP - Feature Control (Part 2)Implements a reusable AUTHORITY-CHECK wrapper class and wires it into a RAP behaviour implementation's Feature Control, both the static global check on Create and the instance-based, partner-scoped checks on Update and Delete, so that an authorization decision greys out an action in the Fiori UI rather than only rejecting it after the save. Part two of the author's Sales App series, it also flags a newer, more strictly typed Feature Control flag SAP introduced since the first article, since using the older type produces a warning and can leave a flag silently without effect.Björn S., published 2026-08-14
Configure an MCP Server Created from an HTTP EndpointConfigure an MCP Server Created from an HTTP EndpointDocuments configuring API Management’s HTTP-source MCP server tools, resources, prompts and policies. Resources are selected from GET operations and have URI templates/content types; prompts define User/Assistant messages with optional arguments, alongside MCP policy configuration.
050: Clean Core Measurement (Preview)050: Clean Core Measurement (Preview)Walks through Clean Core Measurement (CCM), an open-source tool for tracking ABAP Cloud readiness across a system landscape: a dashboard showing Cloud Ready and Upgrade Stable status and a Technical Debt Score per system, runs recorded under administration, and a process area where custom APIs not released by SAP can be documented and excluded from the score. Reporting breaks the score down to individual objects, the unreleased APIs behind them, and which team or product cluster carries the most outstanding work.Björn S., published 2026-08-03
CCM - Calculate Key FiguresCCM - Calculate Key FiguresExplains how the Clean Core Measurement (CCM) project turns ABAP Test Cockpit findings into the Technical Debt Score shown on its Clean Core Dashboard: messages from the ABAP_CLEAN_CORE_READINESS check are weighted by severity level (B/C/D) and summed per object, while the object's overall classification follows its highest message level rather than the point total. Covers where the calculation can be tuned — configurable weights, an exemption process, and additional metrics for documented but unreleased API use — and how the resulting score and classification drive the object list and per-object processing views.Björn S., published 2026-08-05
ABAP - Create dumpABAP - Create dumpShows how to terminate an ABAP program on purpose with RAISE SHORTDUMP — from a freshly created exception instance, or one already caught in a TRY/CATCH where continuing no longer makes sense — so a hard-to-diagnose failure leaves a dump behind instead of running on silently. The second half reads that dump back in ABAP Development Tools for Eclipse: the Feed Reader notification, the compressed view against the classic ST22-style view, and sections such as Active Calls and Source Code Extract, the same ADT troubleshooting path debugging places alongside the ABAP Debugger for ABAP Cloud.Björn S., published 2026-09-11
052: 10 Minutes from Start to Launchpad052: 10 Minutes from Start to LaunchpadWalks a RAP application from a root CDS view entity through a consumption projection and its associations to a metadata extension: a facet per field group, a hidden field via UI.hidden, and a selection field on the ABAP package, all in a Customer-layer DDLX source read by the generated Fiori elements app. It then covers the parts ABAP CDS modelling and annotation stop short of — service definition and binding, generating the UI in Business Application Studio, and wiring the deployed app into the Fiori Launchpad through an IAM App and business catalog.Björn S., published 2026-09-07
RAP - Navigation (App to App)RAP - Navigation (App to App)Walks through app-to-app navigation from a RAP list report and object page: the @Consumption.semanticObject annotation and its semanticObjectMapping.element and additionalBinding variants for links, against the inline @UI.lineItem WITH_INTENT_BASED_NAVIGATION and @UI.identification FOR_INTENT_BASED_NAVIGATION for buttons. Each variant is added through a CDS metadata extension and traced into the target app, showing which fields end up in the filter and how the two annotation styles differ in the list report's formatting. Annotation-driven navigation on a RAP service is part of what Fiori annotations covers on the ABAP door: CDS annotations, carried in a metadata extension, driving the Fiori elements UI.Björn S., published 2026-09-01
051: ABAP Cleaner in VS Code - Installation and Guide051: ABAP Cleaner in VS Code - Installation and GuideWalks through installing ABAP Cleaner inside ABAP Development Tools for VS Code and setting it as the default formatter in place of ADT's Pretty Printer, then using its interactive rule view to compare unformatted and cleaned code and configure which rules run, at class, component or method scope. A worked example applies Clean ABAP rules to one method: removing a redundant me-> self-reference and an unneeded EXPORTING keyword, and restructuring a CHECK statement that the styleguide disallows once other statements precede it.Björn S., published 2026-08-17
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API Policy - FAQAPI Policy - FAQSAP’s June 2026 FAQ, version 1.3, explains the scope and use conditions of the SAP API Policy, including published and non-published APIs, ADT developer access, AI-driven usage and third-party MCP servers. It also addresses data extraction and the responsibilities of customers and partners. The FAQ is informational: it does not modify contracts, and applicable agreements and product documentation prevail if they conflict with it.