DocDocA page in first-party documentation. Its publisher keeps it current, so it cannot go stale — what ages is our reading of it.See every one →SAP Help Portal
Configure an MCP Server Created from an HTTP Endpoint
Documents configuring API ManagementAPI ManagementAPI proxies in front of backend services, with security and traffic management policies attached to them, and Developer Hub where consumers subscribe.sap official, btp’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.
Where it sits
Explains
Serve your application over MCPBTPServe your application over MCPExposing selected application data and business operations to an AI agent through the Model Context Protocol. An application may also integrate remote services through [service integration](capability:service-integration), connecting its exposed contract with [agent access to your systems](capability:agent-systems-access). Development assistance belongs to [agent access to your code](capability:agent-code-access).API ManagementBTPAPI ManagementAPI proxies in front of backend services, with security and traffic management policies attached to them, and Developer Hub where consumers subscribe.
Who is behind it
SAPSAPWrote this
In the atlas: maintains 137, wrote 14@SAPauthor
In the atlas: maintains 137, wrote 14@SAPauthor
Properties
About this work
Published on
For mcp-servers
Covers
HTTP-source MCP server configuration for API tools, GET-derived resources and parameterized prompts.
Applies in
For btp-api-management
Covers
Configuration of an existing HTTP-source MCP server artifact and its resource/prompt definitions.
Applies in
Group by45 of 45 pieces
Piece, what it offersStill applies
CAP in the age of AI #7 - vector embeddings wrap-upCAP in the age of AI #7 - vector embeddings wrap-upThe same embeddings model taken from SQLite to SAP HANA Cloud, then handed to an agent. Locally it is @cap-js/ai that adds the vector functions SQLite lacks and downloads an all-MiniLM L6v2 ONNX model on first start; on HANA natural language processing has to be switched on, the model name is a mandatory argument, the vectors it returns are 768 dimensions, and dimensions must match on both sides of a comparison. HANA itself can be given SAP AI Core as a remote source for other embedding models, which a CDS.ql expression has to inject because the postfix notation only takes what the CDS model holds, and the hour ends with a search function over cosine similarity exposed over @cap-js/mcp, so an agent asked about low output from solar panels calls semantic search instead of writing the query itself.published 2026-10-16
Powering Enterprise-Ready Agentic AI with SAP Integration SuitePowering Enterprise-Ready Agentic AI with SAP Integration SuiteA Devtoberfest 2026 session (INT-31) from SAP Integration Suite product management on the MCP gateway. The demo creates an MCP server in a design package from an API already deployed on the tenant, exposes two of its 300-odd resources as tools, attaches authentication and quota policies on a policies tab, and publishes the deployed endpoint as an AI product in Developer Hub of API Management, where an agent subscribes and receives a token, URL, key and secret; the calls then show up in monitoring, in message processing logs and in the analytics dashboard, which is the MCP exposure and the tool governance the edges rest on. Three AI features inside Cloud Integration follow: a content migration agent that converts a PI/PO Java mapping into a Groovy script and generates a second integration flow for its lookup, memory profiling during a flow simulation, and root-cause analysis on a failed message processing log.SAP Developers, published 2026-10-07
🔴 Your Agent Wants to Call SAP. Now What?🔴 Your Agent Wants to Call SAP. Now What?Devtoberfest 2026 session INT-23, on what belongs between an agent and an SAP system. A solution advisor and an enterprise architect point Joule Desktop extensions at MCP servers built on API Management inside SAP Integration Suite, and ask it for business partners, orders and line items from an S/4HANA demo system; asked for the ten largest customers it answers from a sample of 200 orders rather than reading the whole table. They then open the API proxy behind it, where a spike arrest policy caps the backend at ten calls per second and the MCP server is configured to expose only the GET resources of the business-partner API so that an agent cannot create one, which is where the edges to Serve your application over MCP and Rate limiting hold. For totals across all sales orders they send the agent to SAP Business Data Cloud instead of the transactional system, since it aggregates and is read-only, and back through Integration Suite for writes such as journal entries.SAP Developers, published 2026-09-30
Expose RFCs as MCP Tools in Integration SuiteExpose RFCs as MCP Tools in Integration SuiteWalks through creating an MCP server in SAP Integration Suite from an RFC source: an on-premise RFC destination labelled for Integration Cell inclusion, a search over the backend's function modules (minimum seven characters), and up to 50 selected modules each becoming a tool. Covers the resulting server's configuration (Source, Tools and Prompts, with no Resources section for this source) and the two scopes an RFC-based server's policy adds beyond an API-sourced one, API.invoke and ESBMessaging.send, plus the RFC receiver adapter used at runtime. Demonstrates the flow with a purchase-order scenario where an AI client calls BAPI_PO_CREATE1 and BAPI_PO_GETDETAIL1 as MCP tools.ronit199666, published 2026-09-24
From APIs to Agent Tools: How MCP Gateway changes what Integration meansFrom APIs to Agent Tools: How MCP Gateway changes what Integration meansThe opening session of the Devtoberfest 2026 integration track, in which two product managers for SAP Integration Suite set out why the suite puts an MCP gateway between agents and backend systems, and then build one. The demo turns an HTTP endpoint and its OpenAPI specification into MCP tools on the integration cell runtime, does the same on top of an existing API-centric integration, and shows the policies tab where authentication through an external provider, quotas, spike arrest and IP filtering sit, plus the trace of the JSON-RPC calls in monitoring and the agent they are earmarked against in analytics. That is where the serve your application over MCP and tool governance edges hold; RFCs and BAPIs as sources are stated as supported, and MCP federation, custom domains and edge integration cell as roadmap.SAP Developers, published 2026-09-23
Supercharge Joule Desktop: Connect Any SAP API in Minutes with MCP GatewaySupercharge Joule Desktop: Connect Any SAP API in Minutes with MCP GatewayDevtoberfest 2026 session INT-13, in which an SAP solution advisor connects a live S/4HANA system to the desktop experience of Joule Work through the MCP gateway in SAP Integration Suite. One OpenAPI specification covering business partners, sales orders, material stock, billing and purchase requisitions is uploaded as an MCP server artifact, deployed to integration cell with XSUAA inbound authentication, and registered as an MCP connector; the destination behind it is then switched from basic authentication to principal propagation, and the Cloud Connector monitor shows the same question arriving as the presenter's own user. That demonstration is the serve your application over MCP edge, and the second half is Joule Work itself: a Markdown skill that fixes the steps and format of a customer briefing, and a Space the skill rebuilds with each run.SAP Developers, published 2026-09-23
Create an MCP Server for Enterprise AI AgentsCreate an MCP Server for Enterprise AI AgentsWraps the preceding supply-risk graph from API Composition as an MCP server in Integration Suite, with API Management activated as a prerequisite. The walkthrough selects retrieval tools, deploys on Integration Cell, publishes a product in Developer Hub, creates an agent subscription and invokes the tools in MCP Inspector; its companion tutorial uses mock backends.Shyam, published 2026-09-23
SAP Just Became AI-Agent Ready — Here's a Step-by-Step MCP WalkthroughSAP Just Became AI-Agent Ready — Here's a Step-by-Step MCP WalkthroughBuilds an MCP Server on SAP Integration Suite's Integration Cell, in front of a Cloud Integration flow that passes an OData V4 backend through untouched, with three tools generated from an OpenAPI spec. Secures it with OAuth 2.0 on SAP BTP client_credentials against XSUAA, and walks through the scope mismatch — the service key issues ESBMessaging.send, not the server's default API.invoke — that returns 403 until corrected; the finished server is then registered as a tool in Claude Code.published 2026-09-04
SAP Integration Suite + MCP: A Practical Architecture for AI Agents and SAPSAP Integration Suite + MCP: A Practical Architecture for AI Agents and SAPLays out the runtime chain for exposing S/4HANA APIs to an AI agent through SAP Integration Suite: the agent calls a tool on the MCP Gateway, which is built from a governed API Artifact, which still runs on Cloud Integration for mapping, routing and error handling before reaching the backend. It states that the API-artifact approach requires the Integration Cell runtime rather than the normal CPI message-processing runtime, an OAuth-secured REST or OData artifact on OpenAPI 3.0.0-3.0.3, and an entitlement that is service-plan dependent (citing SAP Note 2903776) — so the architecture question is whether the landscape already has the right MCP entitlement, runtime and API foundation.aayushaggarwal, published 2026-09-02
CAP in the age of AI #3 - from MCP to A2ACAP in the age of AI #3 - from MCP to A2AThe episode that finishes @cap-js/mcp with authorisation and then crosses to agents. @requires and @restrict are the same annotations CAP already has, and the plugin reads them to filter the tool list and the describe output per user and per request, so a model is not told about entities the caller cannot reach — where the OData metadata of the same service lists every exposed entity regardless. The second half annotates a service with @agent from @cap-js/agents, which serves it over A2A with an agent card and a chat preview, runs first against a mocked response and then against SAP AI Core bound with cds bind and a hybrid profile, and reuses the MCP adapter's tools rather than defining new ones.published 2026-08-21
Connecting a Custom MCP Server to Joule Work Desktop: A Seamless and Secure Authentication FlowConnecting a Custom MCP Server to Joule Work Desktop: A Seamless and Secure Authentication FlowWalks through connecting a custom MCP server to Joule Work Desktop: a Dynamic Client Registration handshake (RFC 7591) followed by an Authorization Code + PKCE flow through the organisation's SSO via XSUAA or IAS, so authentication establishes the human identity that Joule then attaches to every subsequent tool call. That forwarded identity lets the BTP backend apply its existing authorization checks and row-level data filtering instead of a second permission model, and a role change in XSUAA revokes access on the next token refresh.published 2026-08-17
RFC/BAPIs Meet AI Agents: Why SAP Integration Suite MCP Server MattersRFC/BAPIs Meet AI Agents: Why SAP Integration Suite MCP Server MattersExplains that SAP Integration Suite's MCP Server artifact can expose RFC-enabled BAPIs, alongside API artifacts and HTTP endpoints, as MCP tools — letting BAPIs on SAP ECC or on-premise S/4HANA participate in agentic workflows without rewriting business logic or waiting for a full ERP transformation. Frames RFC support as a bridge for organisations still modernising rather than a recommendation to build new RFC-based integrations, and notes the exposed BAPIs inherit the server's existing authentication, rate limiting and IP filtering. A demo built against an SAP ECC backend shows an MCP client discovering and invoking several read-only BAPIs from natural-language prompts, with no custom wrapper code.arunmaarirajha_kv, published 2026-07-28
API Composition: Seamless Enterprise Data Access for Developers and AI AgentsAPI Composition: Seamless Enterprise Data Access for Developers and AI AgentsAPI Composition (formerly Graph, a capability of API Management) curates business data graphs from existing SAP and non-SAP API providers, so a query can navigate and expand relationships across systems through one composed API rather than hand-written integration code. Palak walks through combining SAP S/4HANA warehouse-stock data with Everstream Analytics risk data into one API, then exposing that composed API as an MCP server so an AI agent calls it with the same semantic context — the scenario behind API Management's MCP servers coverage.published 2026-07-27
MCP Servers on SAP Integration Suite : Build Your First MCP Server from an APIMCP Servers on SAP Integration Suite : Build Your First MCP Server from an APIWalks through building an MCP server on SAP Integration Suite from an existing managed API — SAP S/4HANA's Purchase Order API — rather than from an HTTP endpoint or an RFC, which the same creation wizard supports but a later post in the series is left to cover. Selected API operations become MCP Tools with generated input and output schemas, the server inherits its Authentication policy from the source API, and a Process Integration Runtime service instance supplies the OAuth credentials an external client needs to invoke it. Ends by connecting the deployed server to Cline in VS Code and having it chain tool calls to answer a natural-language purchase-order query.published 2026-07-15
From SAP Integration Suite iFlow to MCP Tools: Exposing OData APIs to AI AgentsFrom SAP Integration Suite iFlow to MCP Tools: Exposing OData APIs to AI AgentsBuilds an MCP Server artifact inside SAP Integration Suite's Integration Cell runtime that fronts a Northwind OData V4 API through a Cloud Integration iFlow, turning each OpenAPI operation into a tool an agent can call. Walks through the OAuth2 client-credentials flow against XSUAA and the authorization policy scope — ESBMessaging.send in place of the default API.invoke — that gates access to the MCP server, then tests the server from Claude Code.published 2026-07-14
Turn SAP APIs into MCP Tools for AI Agents using SAP Integration Suite Free TrialTurn SAP APIs into MCP Tools for AI Agents using SAP Integration Suite Free TrialWalks through building an MCP server on SAP Integration Suite's free trial from an existing API artifact — the Business Partner API against a public S/4HANA Cloud sandbox — rather than from an HTTP endpoint with an OpenAPI specification or from RFC-enabled function modules, the creation wizard's other two source types, left unexplained here. Covers the API artifact's Content Modifier policy that injects the Business Accelerator Hub API key before the backend call, and the "Trust Upstream MCP Authorization" setting that lets the MCP server delegate authorization checks to that source API instead of duplicating them. Ends by fetching an OAuth token from a Process Integration Runtime service key and pointing an MCP client at the deployed server over streamable HTTP.published 2026-07-13
Building MCP Servers with SAP Integration Suite: What to Design, Not Just How to ConnectBuilding MCP Servers with SAP Integration Suite: What to Design, Not Just How to ConnectArgues that the tool design, not the connection, is the hard part of putting an API in front of an agent. Works one request — create a customer — through eight endpoint-shaped tools, where the agent carries ids between calls and rebuilds the business rules each run, then through a single intent-shaped create_customer that hides the sequence; and says what separates the two: a business operation for a name, parameters a caller can supply without a lookup, the rules in the server rather than the prompt, and a description written for an agent choosing a tool. The SAP Integration Suite half is short — three creation paths, an iFlow behind the API artifact when a tool has to cross systems — and it closes on a checklist to run before publishing.published 2026-07-07
HANA AI Toolkit — Local MCP ServerHANA AI Toolkit — Local MCP ServerAn MCP server that turns the hana-ml Python library into governed tools an agent can call against a HANA Cloud instance, shipped in the hana-ai toolkit and exposed over stdio, SSE and streamable HTTP. Its one firm rule is attributable execution: an audit module writes the MCP-side identity — agent, model, session, tool, redacted arguments — into the HANA connection before any SQL runs, and fails the call if that write fails. A worked example of governance on an MCP tool surface, from SAP's data side rather than CAP's.published 2026-06-15
AI-native North Star architecture — Platform LayerAI-native North Star architecture — Platform LayerThe platform layer of SAP's North Star architecture, the chapter that says where agents run and what a developer builds them with. It names an AI Golden Path built on the SAP Cloud Application Programming Model, the ABAP Cloud development model with RAP and the SAP Fiori design system, and a managed agent runtime on SAP BTP that is designed to provide software development kits for building agents in any framework, an agent sandbox, container-hosted execution, a skills registry and continuous evaluations, which is the ground agent tooling covers. Agents are extended without changing their code through four patterns, the first of them tool extensibility through the Model Context Protocol, the concern MCP servers is named for; the process-layer chapter adds that a pro-code path with a standardised agent SDK and a prompt-driven path through the Joule Studio solution produce the same code artifact on the same runtime. It describes a design SAP intends rather than products that exist, and the SDK and the registry it names have no entry here yet.published 2026-05-13
AI-native North Star architecture — Platform Layer
Agent tooling changed in @cap-js/agents 0.9.1, 2026-08-14. Affects A reference.
Agentic AI on BTP: a Multi‑Agent App with Pydantic AIAgentic AI on BTP: a Multi‑Agent App with Pydantic AISplits a single CAP/TypeScript agent that had grown to juggle five BTP MCP servers behind one bloated tool list into btp-multiagent-app, a Python and Pydantic AI rewrite where the Cloud Foundry and BTP Core MCP servers each get a dedicated specialist agent, with an audit log specialist scaffolded but left disabled, behind an orchestrator whose only tools are delegation calls to those specialists, which is the agent-tooling pattern the piece works through. Each specialist authenticates to its MCP server over Streamable HTTP with OAuth 2.1, and a shared module centralises the SAP AI Core GenAI Hub model setup behind two credential layouts, one for local runs and one for the Cloud Foundry service binding, the LLM integration side of the rewrite. Tool lists per agent drop from well over a hundred to a dozen or two, and routing failures become separable from tool-misuse failures by reading the trace.published 2026-05-03
Agentic AI on BTP: a Single Agent with LangGraphAgentic AI on BTP: a Single Agent with LangGraphA CAP TypeScript agent puts a LangGraph StateGraph in front of AzureOpenAiChatClient from @sap-ai-sdk/langchain, reaching SAP AI Core's Generative AI Hub, and lets its tool-calling loop draw on five deployed MCP servers — OData MCP Proxy, CI MCP Server, AI Core MCP Server, BTP MCP Server and BTP CF MCP Server — through @langchain/mcp-adapters' MultiServerMCPClient. Because agent, servers and APIs share one XSUAA tenant, the chat service forwards the signed-in user's own JWT instead of a service account, so each downstream server enforces that user's own authorizations. Past roughly a hundred combined tools the single prompt slows down and stops separating concerns, which is why the author's next post splits it into one specialist agent per MCP server behind an orchestrator.published 2026-05-03
BTP Audit Log MCP Server: Security Monitoring with AI AssistantsBTP Audit Log MCP Server: Security Monitoring with AI AssistantsWouter Lemaire builds an MCP server over SAP BTP's Audit Log Retrieval API using odata-mcp-proxy, with a single entity set and zero custom code, so an AI assistant can answer natural-language questions like "Were there any configuration changes yesterday?" by calling AuditLogRecords_list against a BTP destination authenticated with the Audit Log service's service key. It covers the destination setup, the entity-set configuration that maps the PascalCase entity name to a lowercase auditlogrecords path, and handling the API's 500-record pagination limit.published 2026-03-13
BTP Cloud Foundry MCP Server: Managing CF Environments with AIBTP Cloud Foundry MCP Server: Managing CF Environments with AIWalks through a server built on odata-mcp-proxy that exposes the Cloud Foundry V3 API's 28 entity sets — apps, orgs, spaces, services, networking, quotas — as MCP tools from a JSON config with no application code. It shows the config shape that bridges the API's snake_case paths to PascalCase tool names via a urlPath field, and the OAuth2 client-credentials destination setup an assistant needs to reach a CF landscape.published 2026-03-13
Graph on Integration Suite: Simplifying Multi-API Data Retrieval with Unified Business Data GraphGraph on Integration Suite: Simplifying Multi-API Data Retrieval with Unified Business Data GraphA hands-on walkthrough of Graph, the API Management feature of SAP Integration Suite also called Business Data Graphs, which exposes several OData APIs as one connected data model behind a single OData V4 or GraphQL endpoint. It covers enabling the capability and its Graph.KeyUser and GraphNavigator.Viewer role collections, creating BTP destinations and a service key for an S/4HANA system, then building a Business Data Graph over the Sales Order and Business Partner APIs so a mirrored SoldToParty association returns both in one call, in place of the two OData requests a Cloud Integration Content Enricher would otherwise merge.published 2026-01-09
SAP PI Migration to BTP Integration Suite Patterns and learning experiencesSAP PI Migration to BTP Integration Suite Patterns and learning experiencesWalks through the integration patterns an SAP PI migration project moved onto SAP Cloud Integration iFlows — API Management proxies fronting calls into on-premise SAP systems over XI/SOAP via Cloud Connector, SFTP transfers, and eventing routes — and the operational lessons from running it: sizing JMS queues, choosing exactly-once JMS queues over Cloud Integration's Data Store for XI receiver adapters and at-least-once JMS for XI sender adapters, and workarounds for gaps in the migration tooling. The API Management proxies handle JWT validation against a non-SAP identity provider, IP filtering and OData-to-OpenAPI conversion in front of the iFlows.saikrishna_kalivarapu2, published 2024-12-04
Information Map – Introduction Series: Graph in SAP Integration SuiteInformation Map – Introduction Series: Graph in SAP Integration SuiteIntroduces Graph, an enhancement to API Management within SAP Integration Suite that gives developers a single API onto an organisation's business systems, modelled as one semantically connected business data graph, later renamed API Composition. Splits the work between an administrator, who enables SAP BTP destinations to the backend systems and builds the business data graph, and a developer, who explores it in the Graph Navigator tool and builds an application against the resulting Graph API.published 2024-02-21
Edge Integration Cell : Design, deploy and manage APIsEdge Integration Cell : Design, deploy and manage APIsWalks through creating an API artifact in API Management on the customer-managed Edge Integration Cell runtime, including the option to generate the artifact by importing an OpenAPI specification rather than from a URL or by hand. It then attaches an Authentication policy and a Quota step capped at four calls per minute, deploys, and shows both the resulting 401 and the quota-breach error in the Monitor logs. The author frames it as the first of a series on Edge Integration Cell's policies.published 2023-11-15
Third-Party MCP Server Access to SAP Solutions on BTPThird-Party MCP Server Access to SAP Solutions on BTPDescribes external MCP servers and custom servers on BTP, assigning their operators responsibility for authentication, scoped identity, API limits, logging and lifecycle. The permitted use remains conditional on the SAP API Policy, while SAP Integration Suite and Joule Studio are described as SAP-provided paths. Hosting a server on BTP does not automatically supply its governance controls.Dhawal Joshi, Harut Ter-Minasyan, Mirko Günther
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.
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.
Agentic CAP: Build MCP servers and enterprise AI agentsAgentic CAP: Build MCP servers and enterprise AI agentsCAP applications become AI agents over the Model Context Protocol and the Agent2Agent protocol, which is the serve your application over MCP concern, and SAP AI Core is the LLM integration through which AI is embedded in a CAP app, with recommendations from the SAP-RPT-1 model as the abstract's example. The abstract names the two protocols and the one model and does not say which packages carry them. A two-hour TechEd 2026 session in a hands-on room (Tuesday 27 October, Berlin), presented by Daniel Hutzel, Daniel Schlachter, Marc Huber and Sami Lechner, written here from SAP's abstract; the recording is not yet published.
MCP Gateway in Practice: Architecture, configuration, and hands-onMCP Gateway in Practice: Architecture, configuration, and hands-onA Devtoberfest 2026 integration-track session (INT-21) on the MCP gateway of SAP Integration Suite: curated enterprise APIs served to agents as MCP tools over JSON-RPC, behind the authentication, authorization and traffic policies an API artifact already carries, with the existing API layer left in place. The hands-on half composes S/4HANA plant, material-stock and supplier data with a non-SAP location-risk source into one business data graph, downloads its OpenAPI specification, creates an MCP server artifact with tools, prompts and a surge-protection policy over that endpoint, and publishes it as a product in Developer Hub of API Management, where an agent developer subscribes and gets OAuth credentials. An MCP client then asks for 15 brake pads and ranks plants by stock, location risk and distance from Walldorf, which is what the agent access to your systems edge rests on; the Q&A covers principal propagation to the backend, how errors reach the model, and which Integration Suite editions carry the gateway.SAP Developers
Modern integration at TÜV Rheinland: APIs, events and cloud transformationModern integration at TÜV Rheinland: APIs, events and cloud transformationTÜV Rheinland's migration from SAP Process Orchestration to SAP Integration Suite with API-led connectivity and event-driven architecture, told through business cases. The abstract names what was used: the SAP Integration Suite, Event Mesh capability, API Management, generative AI for faster development and SAP Cloud ALM for monitoring. It states nothing about how any of them was used, so the edges rest on the names and on the Platform migration the story starts from. A TechEd 2026 session (Wednesday 28 October, Berlin), written here from SAP's abstract; the recording is not yet published.
Road map for SAP Integration Suite: What ships next across all capabilitiesRoad map for SAP Integration Suite: What ships next across all capabilitiesSAP's road map for SAP Integration Suite across its capability areas: API Management, event-driven integration, business process and trading partner integration, and hybrid runtimes for SAP and third-party systems. The abstract promises recent deliveries and the planned innovations that make the platform agent-ready within SAP Business AI Platform; it names the areas and no shipping item, so the edges rest on the product and the one area it names by a product name. A TechEd 2026 session (Thursday 29 October, Berlin; also IN804V, virtual), written here from SAP's abstract; the recording is not yet published.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Details
Graph
Serve your application over MCPcapability, core and community
API Managementartifact
SAP Help Portalpublishing source
Source
History
- Entered the atlasDiscovered via Added by hand.
For your agent
- Ref
content:integration-suite-mcp-http-configuration- JSON
- /content/integration-suite-mcp-http-configuration.json
- MCP
- Connecting an agent