TalkTalkA recorded or written talk.See every one →YouTube — SAP Developers playlists
What's in Daniel Hutzel's brain?
A Devtoberfest 2026 session in the building-apps track, in which Daniel HutzelDaniel Hutzelgave 3 talks, contributed to 32 entriessap official and DJ AdamsDJ Adamscreated 22 pieces, contributed to 20 entriessap official work through what the CAP team is building for agents. A bookshop gets an MCP endpoint beside its OData one from a single annotation, with the plugin writing the coding agent's configuration itself; in the xt-travels sample five services that know nothing about each other are served over MCP and an agent does the orchestration the hand-built UI and its value helps used to do. Hutzel then annotates a service as an agent so the ReAct loop and the choice of model move into the CAP service, and finally drops MCP for a skill that teaches the agent CQL instead, which is where the edges to Serve your application over MCPServe 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, connecting its exposed contract with agent access to your systems. Development assistance belongs to agent access to your code.SAP and community, narrow by design, Agent toolingAgent toolingBuilding an agent into your own application — the tools it may call, the state it keeps between turns, and the framework it runs in. Distinct from MCP servers, which expose an application to somebody else's agent, and from agent guidance, which is knowledge handed to a coding agent.SAP and community, unassessed and Agent guidanceAgent guidancePackaged knowledge you hand a coding agent so it gets a framework right unprompted — skills, rule files, instruction packs. Distinct from agent tooling, which is about building agentic features into your application, and from agent access to your code, where the agent reads the real project instead of being handed a file about it.SAP and community, core adopted it come from. The mechanism under all of it, a plugin file in the package root and event handlers that can be added to any CAP service, is the edge to Plugin authoringPlugin authoringWriting a package that extends a framework or runtime rather than an application that uses it — a reusable extension loaded by its host, and the question you arrive at once solving a problem twice makes you want to solve it once for everyone.SAP only.
Where it sits
Explains
Serve your application over MCPCAPServe 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).Plugin authoringCAPPlugin authoringWriting a package that extends a framework or runtime rather than an application that uses it — a reusable extension loaded by its host, and the question you arrive at once solving a problem twice makes you want to solve it once for everyone.Agent toolingCAPAgent toolingBuilding an agent into your own application — the tools it may call, the state it keeps between turns, and the framework it runs in. Distinct from MCP servers, which expose an application to somebody else's agent, and from agent guidance, which is knowledge handed to a coding agent.Agent guidanceCAPAgent guidancePackaged knowledge you hand a coding agent so it gets a framework right unprompted — skills, rule files, instruction packs. Distinct from agent tooling, which is about building agentic features into your application, and from [agent access to your code](capability:agent-code-access), where the agent reads the real project instead of being handed a file about it.
Who is behind it
Daniel HutzelDaniel HutzelWrote this
In the atlas: contributes to 32, wrote 3@danjoaDJ AdamsDJ AdamsWrote this
Developer Advocate
In the atlas: contributes to 20, wrote 22@qmacroauthors
In the atlas: contributes to 32, wrote 3@danjoaDJ AdamsDJ AdamsWrote this
Developer Advocate
In the atlas: contributes to 20, wrote 22@qmacroauthors
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For mcp-servers
Applies in
For plugin-authoring
Applies in
For agent-tooling
Applies in
For agent-guidance
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Group by69 of 69 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
SAP Meets the Agentic Web: CAP MCP - UI5 WebMCPSAP Meets the Agentic Web: CAP MCP - UI5 WebMCPA Devtoberfest 2026 session (CAP-42) that puts MCP and WebMCP side by side: MCP exposes a backend to an agent, WebMCP exposes the tools of a web page to whatever agent arrives at it, and only Chrome behind a flag and Cloudflare's Kite browser support the second one today. The CAP half starts with two agents scraping a Fiori elements app with Playwright and browser dev tools, then annotates the catalogue service with the MCP protocol through @cap-js/mcp, after which the agent calls the generated describe tool instead of parsing pages. The UI5 half registers a search-authors tool on the browser's model context API inside the same app, with the cross-origin isolation header the API requires, and lists it through the WebMCP Chrome extension — the agent run against it ends on an exhausted Gemini key rather than a result.published 2026-10-16
AI Assisted CAP DevelopmentAI Assisted CAP DevelopmentA Devtoberfest 2026 session (CAP-43) on building CAP applications with a coding agent, in two demos. The first asks the same question twice in a dev container, once with no MCP server configured and once with @cap-js/mcp-server registered: without it the agent answers CAP's semantic search with an outdated vector type and CQL, with its documentation search it writes the built-in vector embedding function and a working similarity query. The second installs the cap-developer plugin from capire/skills, from a Devtoberfest preview branch, and runs its guided-development skill stage by stage — domain model, sample data, services, constraints — each stage reviewed before the next.SAP Developers, published 2026-10-16
Building Code-Based AI Agents on the BAIPBuilding Code-Based AI Agents on the BAIPA Devtoberfest 2026 session on writing the agent yourself rather than configuring one, which is the agent tooling edge: an agent is a model with tools, skills, memory and context around it, and the session reads the code of one built in CAP as a LangGraph state graph, with an agent node that calls the model, a tools node holding the MCP clients, and the edge between them looping until no tool is needed. It then shows the shorter route, a CDS service annotated for the agent protocol with its instructions and skills in an agent.md file. SAP AI Core carries both, with the CAP service in front of it as middleware so the credentials never reach the browser, and that is what cap-agent-ui5-webui is demonstrated against: added as a dependency, it gives the annotated service a UI5 chat interface that can be deployed rather than only previewed. A Python multi-agent application on Cloud Foundry, where an orchestrator delegates to per-stack specialists so no single model sees every tool, closes the session.published 2026-10-09
DRY CAP – Making Sustainable Solutions Through PluginsDRY CAP – Making Sustainable Solutions Through PluginsA Devtoberfest 2026 building-apps session on packaging the things you would otherwise write twice, from in-house API clients and shared data models to validation logic, as a CAP plugin. The presenter builds one live: a cds-plugin.js next to package.json is what makes CAP notice the plugin at all, an index.cds carries a reusable user context and service that the consuming application projects into its own and protects there, and the plugin registers an Express middleware at a chosen step of the bootstrap to put user properties on the request. A feature-flagging plugin his team already uses closes it, and the whole walkthrough is the edge to Plugin authoring.SAP Developers, published 2026-10-02
CAP in the age of AI #5 - agents wrap-upCAP in the age of AI #5 - agents wrap-upThe agents topic closed out on what sits around the agent rather than inside it, now that the documentation has moved into capire. The chat preview's session is persisted in the database rather than kept in memory, traces go out through @cap-js/telemetry to a self-hosted MLflow under the OpenTelemetry conventions for generative AI, and the panel is explicit that @agent reuses the MCP adapter's code programmatically without serving an MCP endpoint. It ends in the xtravels sample, where a travel agent delegates to a hotel-service sub-agent and reaches a separately started flight service over MCP through the service binding CAP resolves anyway. Earlier in the hour the same agent answers from a model running on the presenter's laptop, reached as an OpenAI-compatible endpoint.published 2026-10-02
CAP: The Road Ahead - Simplicity in an AI EraCAP: The Road Ahead - Simplicity in an AI EraDevtoberfest 2026 session CAP10, from the head of SAP's Cloud Application Programming Model: forty minutes of live building rather than slides, on the argument that the cheapest code in an AI project is code nobody has to generate. Claude Code builds an invoice-matching workspace from cds init onwards, and each step is one the framework answers rather than the agent: a 42-line domain model that @sap/cds serves as OData and Fiori elements with a status flow, data privacy and change-tracking annotations that produce audit log entries in the console and would reach the SAP Audit Log service once deployed, an imported S/4HANA supplier data product, and semantic matching from a local embedding model after @cap-js/ai is added. The last three steps are annotations: @mcp beside @odata turns the service into an MCP server that a second Claude session queries through @cap-js/mcp, an agent annotation adds the A2A protocol with an agent card and an audit log entry for the agent task, and a skill file gives the agent the matching policy.SAP Developers, published 2026-09-25
Meet Joule Studio and Build your First AI AgentMeet Joule Studio and Build your First AI AgentA Devtoberfest 2026 session from the product manager of Joule Studio, walking one agent through the whole path the tool defines: an intent, the problem statement and goals a coding agent derives from it, the business context it takes from the SAP knowledge graph, and the solution type it proposes with a stated intent fit. The demo is a collections agent that drafts dunning emails: the product requirements document names the metrics and the human-in-the-loop review, the technical specification lists the artifacts to build — the MCP tools among them — and the build is followed by a business test run against business partner 10001, technical unit tests, and deployment to the managed runtime, where the agent and its MCP server appear as deployed assets. Two points shape how it is used rather than what it produces: every asset is a file, editable in the web editor or in the code view and pushable to git, and the same solution can be built from local pro-code tools; n8n workflows are stated as delivered out of the box inside the studio.SAP Developers, published 2026-09-24
CAP in the age of AI #4 - more on agentsCAP in the age of AI #4 - more on agentsAsking a human first, and telling the agent how to behave. Ordering a book through @cap-js/agents happens without a question being asked; the human-in-the-loop annotation on the action turns the same request into an approve-or-reject step, which the episode follows down to the A2A status update that stores the task in an input-required state in the database — A2A itself being JSON-RPC 2.0 over HTTP with server-sent events for the stream. The rest is instructions on disk: an agents.md in the service's own folder removes the question about how many copies to order, a skill under a skills folder is advertised by its description and read only when the agent decides the case applies, and either file makes the plugin build a deep agent instead of the plain one.published 2026-09-11
From SAP Sales and Service Cloud V2 APIs to AI: Building an MCP Server with CAP Node.jsFrom SAP Sales and Service Cloud V2 APIs to AI: Building an MCP Server with CAP Node.jsA step-by-step CAP Node.js walkthrough that wraps the SAP Sales Cloud V2 Case API as a remote service, then exposes the resulting service over both OData V4 and MCP through a single @protocol: ['odata-v4', 'mcp'] annotation together with @cap-js/mcp's per_action_tool setting. Each CDS action — listCases, getCaseById, createCase, patchCase — becomes its own MCP tool served at /mcp/caseservices, discoverable through tools/list and invoked from a natural-language request.pvsbprasad, published 2026-08-31
From Dashboard to Conversational AI in Minutes: Adding MCP to an Existing CAP ApplicationFrom Dashboard to Conversational AI in Minutes: Adding MCP to an Existing CAP ApplicationA walkthrough of adding @cap-js/mcp to an existing CAP service behind the SuccessFactors Localization Dashboard: two annotations (@odata, @mcp) expose the service over MCP beside its existing OData endpoint, and doc comments added to the 18 entities and their fields are surfaced through the describe tool so a querying model gets business context instead of bare field names. During local development cds watch auto-registers the endpoint in ~/.claude.json, and the author connects the same endpoint to Joule Work Desktop as an MCP connector so users can ask coverage questions in natural language.i533678, published 2026-08-24
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
MCP Servers are the New Z-TablesMCP Servers are the New Z-TablesA single CAP service exposed as three overlapping MCP servers tools, queried by the same prompt nineteen times, returned the same tool every time — evidence, the author argues, that tool selection rests on the resemblance between a prompt and a tool's description rather than on any binding a where-used list could enumerate before retiring it. It contrasts that setup with @cap-js/mcp, which exposes a whole service as three generic tools instead of one per operation, and quotes the adapter's own beta documentation admitting no rate limiting, audit logging, input validation or approval workflow, and no use as a gateway to SAP Application APIs. From there it names four small Tool governance practices it has adopted: an owner recorded in the tool's own metadata, logging every invocation, deprecating inside the description, and exposing fewer tools.published 2026-08-21
Adapting SAP Joule for Purchase Order Creation from an Existing Purchase RequisitionAdapting SAP Joule for Purchase Order Creation from an Existing Purchase RequisitionA custom Joule Agent and Joule Skill, built in Joule Studio, classic edition to extend SAP Joule past its built-in Purchase Order display and change features: a buyer's single sentence naming a Purchase Requisition number becomes a created Purchase Order, with the skill wrapping the Purchase Requisition and Purchase Order OData V4 APIs as Action Packages reached through two destinations. The author anchors the agent's success condition to a PurchaseOrderNumber in the skill's output rather than an HTTP status code, and reports that the Purchase Requisition item structure does not map one-to-one onto the Purchase Order creation payload.jonathanvi59, published 2026-08-19
CAP in the age of AI #2 - more on the MCP adapterCAP in the age of AI #2 - more on the MCP adapterWhat the query tool costs in tokens, and the third tool @cap-js/mcp registers. Counted against a model running locally under llama.cpp, the same query is 26 tokens as CQL and 173 as CQN, and the tool definition sent with every system prompt drops from around 5,500 tokens to around 600 — the reason CQL became the default format. The call tool then exposes a service's unbound actions and functions, as one generic tool or, behind a flag, one tool per action with its own description and input schema; a question from the chat about extension points gets the answer that the adapter does the tools, which the panel calls a small subset of the protocol.published 2026-08-14
Add MCP capabilities to a CAP serviceAdd MCP capabilities to a CAP serviceA fifteen-minute walkthrough of turning a plain CAP service into an MCP server: annotate the service with @mcp, install @cap-js/mcp, and it is served alongside OData at /mcp/<path>. The part worth reading it for is what happens next — cds watch writes the endpoint into the local agent's own configuration file, so OpenCode or Claude Code can call the service without anyone editing JSON by hand. It is built on the tiny-sample facet, so there is nothing to prepare, and it shows the protocol traffic rather than only the result. Written while the adapter was in beta, and it says so.published 2026-08-13
CAP in the age of AI #1 - the MCP adapterCAP in the age of AI #1 - the MCP adapterThe episode that opens the series and the first pass over @cap-js/mcp, with four of the people building it on the call. Two of the adapter's tools are worked through: describe, the one an MCP client reaches for first to get the overview of what it may do, and query, which the panel establishes as read-only. It also writes the server entry into a local agent's own configuration file, which episode three comes back to as auto-wiring.published 2026-08-07
CAP in the age of AICAP in the age of AISeven live episodes of Hands-on SAP Dev in which DJ Adams works through CAP's AI features with the people who build them, each one a screen-share against a sample project. The first three are @cap-js/mcp: the @mcp annotation on a service, the describe, query and call tools, CQL as the query format, and what authorisation takes out of the tool list. From episode three the run moves to A2A and @cap-js/agents — human approval of an action, agents.md and skills, session persistence, telemetry and sub-agents — and the last two episodes are vector embeddings in CDS, local on SQLite and native on SAP HANA Cloud.published 2026-08-07
Expose S/4HANA Cloud OData API as an MCP Server via CAP Node.jsExpose S/4HANA Cloud OData API as an MCP Server via CAP Node.jsA CAP Node.js service imports the S/4HANA Cloud Outbound Delivery OData v2 API's EDMX metadata with cds import, proxies its reads and a custom createDelivery action against it, and annotates the service @protocol: ['odata-v4', 'mcp'] with @cap-js/mcp's per_action_tool setting on, so the custom action gets its own MCP tool rather than one generic call_action. It tests the result with raw JSON-RPC tools/list and tools/call requests before deploying to SAP BTP, Cloud Foundry Runtime.Jacky Liu, published 2026-07-29
Expose S/4HANA Cloud OData API as an MCP Server via CAP Node.jsExpose S/4HANA Cloud OData API as an MCP Server via CAP Node.jsA step-by-step walkthrough that wraps SAP S/4HANA Cloud's Outbound Delivery OData v2 API in a CAP Node.js service and exposes it through @cap-js/mcp, so an MCP client can list the generated tools, query the delivery entities and call a custom createDelivery action over JSON-RPC. The remote S/4HANA connection is configured two ways in package.json: direct Basic Authentication credentials for local hybrid testing, and a named BTP destination for the app once deployed to Cloud Foundry.Jacky_Liu1, published 2026-07-29
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
Building Durable AI Agents - Announcing the cds-langgraph-persistence PluginBuilding Durable AI Agents - Announcing the cds-langgraph-persistence PluginThe announcement, and the argument behind it. Treating an agent as a software architecture rather than a model with tools makes a list of production requirements — identity, authn and authz, multitenancy, persistence, event-driven flows, scalability, observability, CI/CD — and the author's point is that CAP already answers most of them for BTP, which is what makes LangGraph inside CAP Node.js worth doing. The post then narrows to one of those requirements, durability, and the checkpointer that supplies it. Written from a year of building agents next to real business systems rather than as a framework tour.merbinjanselm, published 2026-07-15
Building Durable AI Agents - Announcing the cds-langgraph-persistence Plugin
@mi8y/cds-langgraph-persistence has been through 3 major lines since this was published: 0.5 (2026-07), 0.6 (2026-07), 0.7 (2026-09). Affects Runnable code.
The Easiest Way to Expose a CAP Node.js Project as an MCP ServerThe Easiest Way to Expose a CAP Node.js Project as an MCP ServerFrom cds init to a running MCP server in a handful of steps, ending at the MCP Inspector so the result is something you can see rather than something you have to trust. The claim it makes for the plugin is the absence of work: no REST wiring by hand, the CAP application exposed as a server because the package is installed. A walkthrough rather than an argument — the reasoning about what should be exposed lives elsewhere.Jacky Liu, published 2026-07-03
Natural Language Queries for SAP CAP via MCP: The LLM Translates, CDS ExecutesNatural Language Queries for SAP CAP via MCP: The LLM Translates, CDS ExecutesThe division of labour is the argument, and it is in the subtitle: the model turns English into a CDS query and CDS runs it, so nothing generates SQL and nothing hallucinates a join. Schema annotations do the resolving. Long, with the package, the repository and the MCP registry entry all linked.Shahid, published 2026-06-25
Banking Sentinel: A Multi-Agent Credit-Risk Copilot on SAP BTP, Built on a Mixed AI StackBanking Sentinel: A Multi-Agent Credit-Risk Copilot on SAP BTP, Built on a Mixed AI StackThe risk it is chasing is a graph problem stated in banking terms: a borrower who looks safe alone and is the linchpin of a group ten times the size. Multi-agent, mixed AI stack, on BTP and CAP.Shahid, published 2026-06-24
Banking Sentinel: A Multi-Agent Credit-Risk Copilot on SAP BTP, Built on a Mixed AI Stack
Agent tooling changed in @cap-js/agents 0.9.1, 2026-08-14. Affects A recipe, Runnable code.
Teaching AI Agents Best Practices: A Skills Workspace for CAP DevelopmentTeaching AI Agents Best Practices: A Skills Workspace for CAP DevelopmentStates the gap this capability exists for more precisely than most: an agent already knows CAP well enough to generate models, handlers and deployments, but knowing a framework and following its current practice reliably are different things, because a model defaults to whatever it saw most of during training — which may be outdated, subtly wrong, or simply not how a given team works. Skills are offered as the closing mechanism, and the post describes a workspace pattern rather than a single file, with the architecture claimed to be framework-agnostic.daniel_schlachter, published 2026-06-09
Building an LLM Agent in CAP Java with Spring AIBuilding an LLM Agent in CAP Java with Spring AIThe Java counterpart to the author's own Node.js post, and written as one: connecting to AI Core with the SAP AI SDK, then calling an agent and a tool through Spring AI. Opens with a section on libraries and workflows — which framework does what, and what is left to you — before any code.published 2026-06-08
Building an LLM Agent in CAP Java with Spring AI
Agent tooling changed in @cap-js/agents 0.9.1, 2026-08-14. Affects Runnable code.
Building an LLM Agent using CAPBuilding an LLM Agent using CAPThe argument is that CAP is already most of what an agent framework wants — services, handlers, a typed model — so the agent is built inside it rather than beside it. AI Core through sap-ai-sdk, then Langchain for the agent and its tools. Long, with a TLDR at the top for people who want the shape without the walk.published 2026-05-27
Building an LLM Agent using CAP
Agent tooling changed in @cap-js/agents 0.9.1, 2026-08-14. Affects Runnable code.
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
Integrating and Extending JouleIntegrating and Extending JouleSAP's reference architecture for SAP Joule across SAP cloud applications: a request is checked against a Scenario Catalog of the applications' skills and a Knowledge Catalog answered by retrieval-augmented generation, combined with the user's roles and history, sent to an LLM available through the generative AI hub, and, where a Joule function is needed, turned into a call to the backend. Its identity page is the authentication path: each user sits in the Identity Directory of Cloud Identity Services with a Global User ID, Identity Provisioning synchronises role assignments into SAP Build Work Zone, whose navigation service decides which functions a user may call, and the Destination service exchanges the user's token to call a function in the user's name. Its extension page covers Joule Studio in SAP Build, where Joule skills automate rule-based tasks over APIs and AI agents plan and reason with models and document grounding from SAP AI Core, the ground agent tooling covers; a later Joule Studio page describes a managed Joule Studio Runtime on the SAP Business AI Platform, which has no entry here.published 2026-03-16
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
Github Copilot VSCode - My Own SAP Development RulesGithub Copilot VSCode - My Own SAP Development RulesOne developer's rule files for Copilot, split by concern rather than kept as one prompt: CAP backend rules, UI5 frontend rules, Jest testing rules and Bruno collection rules, each with a scope narrow enough that an agent cannot read it two ways. The CAP file covers reusable types, managed data, soft-delete behaviour and service conventions; the UI5 file covers naming, view constraints and where annotations may live. It is the rule-file half of agent guidance rather than the skill half — nothing is packaged or published, and the value on offer is the shape of the split.radu_simen, published 2026-02-05
UI5 MCP Server Got Extended for UI Integration Cards GenerationUI5 MCP Server Got Extended for UI Integration Cards GenerationVersion 0.2.1 of the UI5 MCP Server adds three tools for UI Integration Cards: get_integration_cards_guidelines feeds an agent current best practices and API versions, create_integration_card scaffolds a new card project, and run_manifest_validation checks the generated manifest against the schema. The post frames these as closing the same gaps as the server's existing tools — an LLM's outdated or wrong card API knowledge — this time for scaffolding and validating a card rather than a full app.daniel_vladinov, published 2026-01-22
Event Driven SAP CAP on Kyma with Agentic AI and UI Auto RefreshEvent Driven SAP CAP on Kyma with Agentic AI and UI Auto RefreshA prototype, described as one: a plain CAP application made to react to external events on Kyma, with an agent in the loop and the UI refreshing itself rather than being reloaded. Short — it reports what was built and why, not how to rebuild it.Shahid, published 2025-12-01
How Redwood Software and SAP are shaping the next era of automation with Joule StudioHow Redwood Software and SAP are shaping the next era of automation with Joule StudioRedwood's Field CTO describes a tech preview where an SAP Basis administrator tells SAP Joule in natural language to pause background jobs and dependent Integration Suite iFlows for unplanned system maintenance; Joule acts as a control tower, triggering a pre-approved RunMyJobs workflow and asking for approval before the restart proceeds. The integration is built by publishing RunMyJobs operations to the SAP Business Accelerator Hub, securing access through SAP BTP with API keys and role-based permissions, and combining those actions into a skill inside Joule Studio's low-code design canvas.gmblom, published 2025-11-02
Building a CAP service with cds‑mcp and Cline — HANDS‑ON SUPER BASIC GUIDE [ with screenshots ] 🍌Building a CAP service with cds‑mcp and Cline — HANDS‑ON SUPER BASIC GUIDE [ with screenshots ] 🍌Somebody following the CAP MCP server announcement all the way through, and writing down what it cost: a CAP service in VS Code wired to S/4HANA through a destination, plus the real bumps — Windows PATH and global installs — that the announcement does not have.smarchesini, published 2025-09-21
Enhancing Unit Testing in SAP CAP Java Applications with GitHub CopilotEnhancing Unit Testing in SAP CAP Java Applications with GitHub CopilotBuilt on SAP's own CAP Java unit-testing guide, and the question is narrow: how much of that does an assistant actually write for you. The author's own getting-started post is the one to read first.Anjali_Pathak, published 2025-09-04
⚡Unlocking the Power of LLMs in CAP: Understanding llms.txt and llms-full.txt⚡Unlocking the Power of LLMs in CAP: Understanding llms.txt and llms-full.txtllms.txt and llms-full.txt for CAP — a plain-text map of the documentation, written for an agent that arrived by fetching a URL rather than one somebody configured. The convention the atlas uses for itself, applied to capire.Yogananda, published 2025-05-18
Create your first CAP pluginCreate your first CAP pluginA step-by-step guide to the cds-plugin.js extension point: scaffold a package, add an index.cds for shared model artifacts, and test it locally against a throwaway CAP project before publishing to npm, with a separate section on building the same plugin in TypeScript and compiling it with tsc. Points to the author's own cds-plugin-handlers and ui5-cap-serverside-rendering-plugin as worked examples.published 2024-12-09
SAP AI Services - DOX - Gen AI with SAP CAP Plugin - Part 3SAP AI Services - DOX - Gen AI with SAP CAP Plugin - Part 3Building on Reusable components for CAP with cds-plugin by Daniel Schlachter, this part walks through a custom CAP plugin — a cds-plugin.js plus a lib_cap_dox.js helper — that authenticates against SAP's Document Information Extraction (DOX) service and calls its schema and job-status APIs to fill an entity from extracted document fields. It covers reading the service key from Cloud Foundry (cf service-key) for the OAuth token endpoint, and dynamically mapping DOX's header and line-item output onto CAP entity properties.sabarna17, published 2024-06-11
How to build reusable plugin components for CAP Java applicationsHow to build reusable plugin components for CAP Java applicationsA companion to Daniel Schlachter's Reusable components for CAP with cds-plugin, showing the same mechanism on CAP Java: a plugin ships as its own Maven artifact with an event handler and a CdsRuntimeConfiguration implementation, registered through the JDK's ServiceLoader rather than any CAP-specific wiring. The walkthrough builds a cds-emoji-plugin-java jar that decorates @emoji-annotated fields on read, installs it to the local Maven repository, and adds it as a runtime dependency to a cds init --add java bookshop application. It argues the plugin mechanism was not new to CAP Java, just previously undocumented.robinjayasinghe, published 2023-05-16
BTP CAP : Custom plugin to separate generic change log capture logicBTP CAP : Custom plugin to separate generic change log capture logicWalks through building a custom [CAP](ecosystem:cap) plugin that centralises change-log capture: on cds.once('served') it collects entities annotated @audit, then hooks srv.before('UPDATE') to read the existing record, diff it field by field against the incoming payload, and record old/new values with the user and timestamp. It also documents a cds build failure packaging the plugin's own directory into gen/srv for MTA deployment, fixed by adding it as a copyfiles build-parameter step in mta.yaml.sreehari_vpillai, published 2023-05-10
Reusable components for CAP with cds-pluginReusable components for CAP with cds-pluginThe post that taught the mechanism, and it teaches it by picking a requirement small enough to be absurd: every string a service returns should end in a random emoji. Working through that on the bookshop example leaves nothing to argue about except the plumbing, which is the point — what a cds-plugin is, where it hooks in, and why packaging it beats copying it into the next project. Vinícius Barrionuevo credits this post as the thing that gave him the idea for sap-cap-sdm-plugin, and it is hard to read the plugin ecosystem in this graph without it.published 2023-04-30
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 Adapter — CAP guideModel Context Protocol Adapter — CAP guideDocuments @cap-js/mcp and com.sap.cds:cds-adapter-mcp, service annotations, generated describe/query/call tools and local client setup. The guide records Java doc-comment configuration, unbound-action-based data changes, incomplete XSUAA PKCE support and the adapter’s governance boundaries.
CAP Node.js Expert Session #6 - The MCP AdapterCAP Node.js Expert Session #6 - The MCP AdapterDaniel Schlachter and DJ Adams add @cap-js/mcp to a bookshop service, inspect its describe, query and action tools, and query the catalogue through an AI agent. The session distinguishes this runtime adapter from the development-time MCP server and demonstrates automatic registration of the running service with a local agent. The recording describes the adapter as beta in July 2026, with read-only queries and writes through unbound actions.
Examine the details of the Model Context Protocol on startupExamine the details of the Model Context Protocol on startupWhat the MCP adapter actually does when a CAP server boots, watched rather than described — the companion to the tutorial that switches it on.
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.
AI needs a foundation: A map of the plug-in ecosystem for CAPAI needs a foundation: A map of the plug-in ecosystem for CAPA map of the plug-ins for CAP (@sap/cds), official, community and independent, drawn across regions such as integration, performance and tooling, so that a team can see what exists to reuse and what it would have to build: the question plugin authoring answers from the other side. SAP's abstract places CAP at the centre of its AI strategy, with model context protocol support, and the map is offered as the foundation under that. A TechEd 2026 session (Tuesday 27 October, Community Theater, Berlin), presented by Mike Zaschka, written here from SAP's abstract; the recording is not yet published.
Generate agentic workflows using SAP-managed n8n in Joule StudioGenerate agentic workflows using SAP-managed n8n in Joule StudioSAP-managed n8n inside Joule Studio generates a workflow from a business intent a developer states, and the workflow is then tested and deployed, consuming line-of-business application APIs, events and agents in SAP Business AI Platform: process automation with the workflow generated from intent, and agent tooling where the workflow calls agents. The generated workflow sends notifications to the Joule Work mobile app of SAP Joule, to Microsoft Teams or to Slack. SAP's abstract names the pieces and not how the generation or the n8n hosting works. A two-hour hands-on TechEd 2026 session (Tuesday 27 October, Berlin), presented by Rama Sulakshani Murari, Rumen Dimitrov, Seshadri Sreenivas Ramanarayanan and Venugopal Chembrakalathil, written here from SAP's abstract; the recording is not yet published.
Connecting AI agents to the ABAP RESTful application programming modelConnecting AI agents to the ABAP RESTful application programming modelJoule Studio, classic edition connects Joule Agents to applications built with the ABAP RESTful application programming model through actions and skills, calling the OData services those applications expose their business objects through: the tools an agent may call, which is the agent tooling concern seen from the ABAP side. The abstract promises alternative integration patterns and does not name them. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Leon Karlau, written here from SAP's abstract; the recording is not yet published.
Building agentic applications with SAP HANA CloudBuilding agentic applications with SAP HANA CloudA CAP application extended with semantic search and agent features on top of SAP HANA Cloud's vector engine and SAP AI Core, built in a hands-on workshop. The abstract names the parts, CAP, the vector engine and AI Core, and the two additions: semantic search, the retrieval half of retrieval-augmented generation, and LLM-supported agent capabilities inside the application, which is agent tooling. Which embedding model, which CAP runtime and how the agent calls its tools are not stated. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Hui Li, Ritty Joseph, Shraddha Shetty and Tanuja Jadhav, written here from SAP's abstract; the recording is not yet published.
Agentic memory: Knowledge graph engine and recall in SAP HANA CloudAgentic memory: Knowledge graph engine and recall in SAP HANA CloudThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA263 on Wednesday 28 October is a two-hour hands-on on the same engine with a different cast. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Markus Fath and Shraddha Shetty, written here from SAP's abstract; the recording is not yet published.
Knowledge graph and agent memory: Build an agent that remembersKnowledge graph and agent memory: Build an agent that remembersThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA205 on Tuesday 27 October is the 45-minute talk on the same engine, with a near-identical abstract and a different cast. A two-hour hands-on TechEd 2026 session (Wednesday 28 October, Berlin), presented by Christoph Morgen, Jan Zwickel, Markus Fath and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
Agentic Engineering for SAP BTP ExtensionsAgentic Engineering for SAP BTP ExtensionsAn agent harness coordinates code generation across isolated Git worktrees, using a skills registry, SAP CAP MCP Server, Fiori MCP Server and UI5 Web Components MCP Server for development context. The diagram shows LiteLLM as a model proxy in front of SAP AI Core, while automated checks and review gate the generated changes. The worked scenario is CAP-based extensions on BTP, with specifications written before generation and reusable skills governed across teams.
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
CAP in the age of AI #5 - agents wrap-upCAP in the age of AI #5 - agents wrap-upThe agents topic closed out on what sits around the agent rather than inside it, now that the documentation has moved into capire. The chat preview's session is persisted in the database rather than kept in memory, traces go out through @cap-js/telemetry to a self-hosted MLflow under the OpenTelemetry conventions for generative AI, and the panel is explicit that @agent reuses the MCP adapter's code programmatically without serving an MCP endpoint. It ends in the xtravels sample, where a travel agent delegates to a hotel-service sub-agent and reaches a separately started flight service over MCP through the service binding CAP resolves anyway. Earlier in the hour the same agent answers from a model running on the presenter's laptop, reached as an OpenAI-compatible endpoint.published 2026-10-02
CAP in the age of AI #4 - more on agentsCAP in the age of AI #4 - more on agentsAsking a human first, and telling the agent how to behave. Ordering a book through @cap-js/agents happens without a question being asked; the human-in-the-loop annotation on the action turns the same request into an approve-or-reject step, which the episode follows down to the A2A status update that stores the task in an input-required state in the database — A2A itself being JSON-RPC 2.0 over HTTP with server-sent events for the stream. The rest is instructions on disk: an agents.md in the service's own folder removes the question about how many copies to order, a skill under a skills folder is advertised by its description and read only when the agent decides the case applies, and either file makes the plugin build a deep agent instead of the plain one.published 2026-09-11
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
CAP in the age of AI #2 - more on the MCP adapterCAP in the age of AI #2 - more on the MCP adapterWhat the query tool costs in tokens, and the third tool @cap-js/mcp registers. Counted against a model running locally under llama.cpp, the same query is 26 tokens as CQL and 173 as CQN, and the tool definition sent with every system prompt drops from around 5,500 tokens to around 600 — the reason CQL became the default format. The call tool then exposes a service's unbound actions and functions, as one generic tool or, behind a flag, one tool per action with its own description and input schema; a question from the chat about extension points gets the answer that the adapter does the tools, which the panel calls a small subset of the protocol.published 2026-08-14
Add MCP capabilities to a CAP serviceAdd MCP capabilities to a CAP serviceA fifteen-minute walkthrough of turning a plain CAP service into an MCP server: annotate the service with @mcp, install @cap-js/mcp, and it is served alongside OData at /mcp/<path>. The part worth reading it for is what happens next — cds watch writes the endpoint into the local agent's own configuration file, so OpenCode or Claude Code can call the service without anyone editing JSON by hand. It is built on the tiny-sample facet, so there is nothing to prepare, and it shows the protocol traffic rather than only the result. Written while the adapter was in beta, and it says so.published 2026-08-13
CAP in the age of AI #1 - the MCP adapterCAP in the age of AI #1 - the MCP adapterThe episode that opens the series and the first pass over @cap-js/mcp, with four of the people building it on the call. Two of the adapter's tools are worked through: describe, the one an MCP client reaches for first to get the overview of what it may do, and query, which the panel establishes as read-only. It also writes the server entry into a local agent's own configuration file, which episode three comes back to as auto-wiring.published 2026-08-07
CAP in the age of AICAP in the age of AISeven live episodes of Hands-on SAP Dev in which DJ Adams works through CAP's AI features with the people who build them, each one a screen-share against a sample project. The first three are @cap-js/mcp: the @mcp annotation on a service, the describe, query and call tools, CQL as the query format, and what authorisation takes out of the tool list. From episode three the run moves to A2A and @cap-js/agents — human approval of an action, agents.md and skills, session persistence, telemetry and sub-agents — and the last two episodes are vector embeddings in CDS, local on SQLite and native on SAP HANA Cloud.published 2026-08-07
CAP Node.js Expert Session #6 - The MCP AdapterCAP Node.js Expert Session #6 - The MCP AdapterDaniel Schlachter and DJ Adams add @cap-js/mcp to a bookshop service, inspect its describe, query and action tools, and query the catalogue through an AI agent. The session distinguishes this runtime adapter from the development-time MCP server and demonstrates automatic registration of the running service with a local agent. The recording describes the adapter as beta in July 2026, with read-only queries and writes through unbound actions.
Examine the details of the Model Context Protocol on startupExamine the details of the Model Context Protocol on startupWhat the MCP adapter actually does when a CAP server boots, watched rather than described — the companion to the tutorial that switches it on.
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.
Everything new: Try out the latest features in CAPEverything new: Try out the latest features in CAPCAP (@sap/cds) gains the features this hands-on session works through: declarative constraints, which is the input validation concern, status flows as status transition flows, a cds REPL, extensibility through @sap/cds-oyster, and HCQL, which SAP's abstract calls CAP's native query-over-HTTP protocol, after an opening stretch of AI-driven app development. The abstract names the features and stops there; what each one does is not described. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Daniel Hutzel, Daniel Schlachter, Marc Huber and Tim Back, written here from SAP's abstract; the recording is not yet published.
CAP in the age of AI #6 - vector embeddingsCAP in the age of AI #6 - vector embeddingsVector embeddings put to work in the incident management sample, answering whether this problem has been seen before. An embedding element of type Vector is calculated and stored from the vector_embedding function, so the database refreshes it whenever the text behind it changes, and cosine_similarity compares it with a freshly embedded string; because a title says little, a scheduled action first summarises each incident's conversation through a model on SAP AI Core and the embedding is taken from that summary. The similar-incidents list is a view joining incidents to themselves, with order and limit set in a before handler on the expanded query, and the vector element excluded from the service, since OData knows nothing about vectors — on SAP HANA Cloud the function is native, while SQLite needs packages added to the project.published 2026-10-09
Custom Business Logic Extensibility in CAP (CDS-Oyster)Custom Business Logic Extensibility in CAP (CDS-Oyster)A Devtoberfest 2026 session walking @sap/cds-oyster — at version 0.55, with 1.0 stated for Q4 — end to end on a multitenant xtravels, from the application developer's side and the extension developer's side. The application developer adds a submit-for-review action to the status flow and opens exactly one surface for custom code: a separate extension service marked as extensible code, holding a no-op validate action and two read-only helper entities, which the host application calls before the status change; nothing else is extensible, because the annotation defaults to false. The extension developer works in a project whose base model came from cds pull, with test data, a server.js and types from @cap-js/cds-typer added so the UI and code completion work, debugs the handler locally and pushes it as an @sap/cds-mtxs extension, after which the next request rejects a travel over the policy limit without a restart — the code having been stored as an annotation in the tenant's model and run in a Rust WebAssembly sandbox with no database connection, whose queries go back to the CAP runtime as CQL strings, which is tenant extensibility extended from fields to logic.published 2026-10-09
Avoid design time CAP server restarts when maintaining local data filesAvoid design time CAP server restarts when maintaining local data filescds watch restarting on every file change is the feature; this is the case where it is not. Editing a CSV seed file mid-edit restarts the server against half-finished data, and the post is about suppressing that without giving up the watch loop. A small friction most people work around silently rather than fix.published 2024-04-26
Avoid design time CAP server restarts when maintaining local data files
Local development changed in @sap/cds-dk 7.9.1, 2024-05-02. Affects Runnable code.
CAP, CDS, CDL, CSN and jq - finding associationsCAP, CDS, CDL, CSN and jq - finding associationsHow associations are actually represented once CDL is compiled into CSN, worked out by parsing the machine-readable form with jq. Useful less as a recipe than as a way in: anything that wants to reason about a CDS model without the compiler has to read CSN, and this is what that looks like from the outside.published 2024-04-16
CAP, CORS and custom headersCAP, CORS and custom headersWhat CAP itself does about CORS, and where it stops. The starting point is a colleague's request and a deliberate constraint: @sap/approuter has full CORS support, but the author wanted to know what the CAP server offers on its own and how to extend it. Ends up covering preflight requests and custom servers, which is the mechanism a frontend hosted outside BTP actually runs into.published 2024-04-11
ISO content for common CAP typesISO content for common CAP typesThe npm package that supplies ISO-standard content — countries, languages, currencies, timezones — for CAP's common types, and how it works underneath. The author flags the length and the reason for it up front, having followed the mechanism further than the question required, which is what makes it worth reading rather than a package announcement.published 2024-03-14
ISO content for common CAP types
Seed data changed in @sap/cds-dk 7.9.1, 2024-05-02. Affects Runnable code.
CAP is important because it's not importantCAP is important because it's not importantAn essay rather than a technique: what CAP actually is, what it gives you, and the case for treating it as foundational precisely because it is not the interesting part of an application. Written in 2019, when that argument still had to be made, and the title is the argument. Also recorded as a Tech Aloud podcast episode and a CodeTalk, both linked from the post.published 2019-11-06
Computed field example in CAPComputed field example in CAPAn answer to a Community question — how to count the entities on the far side of an association — written up as a short post rather than left in a thread. The answer combines CDS with Node.js service events, which is the seam worth noticing: some of what looks like modelling is expressed in the model and some has to be computed when the request arrives, and the boundary between them is not obvious from either side.published 2019-08-21
Computed field example in CAP
Data modelling has changed 3 times since this was published, most recently in @sap/cds 9.9.0, 2026-04-23. Affects A recipe, Runnable code.
Set up VS Code on Chrome OS for local Application Programming Model developmentSet up VS Code on Chrome OS for local Application Programming Model developmentA CAP development environment on a Chromebook, written from preference rather than constraint — the author sets out why Chrome OS is his primary machine before showing the setup. Carries its own updates section noting what has changed since, which for a 2018 post about an operating system is most of it. The interest now is that local CAP development was portable this early.published 2018-10-16
Set up VS Code on Chrome OS for local Application Programming Model development
Local development has changed twice since this was published, most recently in @sap/cds-dk 7.9.1, 2024-05-02. Affects Runnable code.
SAP Cloud Application Programming Model (CAP) - start hereSAP Cloud Application Programming Model (CAP) - start hereThe orientation post for CAP, published in 2018 and revised in 2020 and again in 2021 with help credited to Iwona Hahn — which is the unusual part: a starting-point index that was maintained rather than left to rot, and says so at the top. Read as the shape of what a newcomer was pointed at, and as a marker of how much of that changed inside three years.published 2018-10-10
Define, generate, deploy: AI-driven spec-first TerraformDefine, generate, deploy: AI-driven spec-first TerraformAccount provisioning written as a spec first: the abstract has participants write a structured description of a BTP account, its subaccounts, entitlements, governance, best practices and more, and an AI turns it into Terraform scripts that build it. The abstract does not name the Terraform provider the scripts use, the spec format or the AI behind the generation. A hands-on TechEd 2026 session (Wednesday 28 October, Berlin), presented by Christian Lechner, DJ Adams, Piotr Tesny and Vipin VijayKumar, written here from SAP's abstract; the recording is not yet published.
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Serve your application over MCPcapability, core and community
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Agent toolingcapability, core and community
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YouTube — SAP Developers playlistspublishing source
YouTube — SAP Developers playlistsdevtoberfest-2026
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