MCP serverMCP servertypeExposes tools to a coding agent over MCP.See every one →What this type is →by SAPby SAPoriginPublished by SAP itself. A visible facet, never an input to a reading — a dormant official plugin reads exactly like a dormant independent one.See every one →

@cap-js/mcp-server

SAP's MCP server for CAP development, run as cds-mcp: search_model searches the project's compiled CDS model, search_docs searches the CAP documentation indexed as embeddings on the developer's own machine.

A coding agent asked to change a CAP project answers from what it remembers about CAP and from whichever .cds files it happened to open. This server gives it two tools instead: search_model fuzzy-matches names in the compiled CDS model, which carries every definition with its annotations and the HTTP endpoints the services are served at, and search_docs runs a semantic search over preprocessed CAP documentation held as embeddings on the machine the server runs on. It is registered with the MCP client rather than added to the project: the client starts npx -y @cap-js/mcp-server, for which the README shows the configuration in VS Code, Claude Code, OpenAI Codex and opencode, and two rules to paste into AGENTS.md are what tell the model to search before it proposes a change. Installed globally it is also a command, so cds-mcp search_docs and cds-mcp search_model answer the same two questions from a terminal. Both tools read; what the agent then writes is the agent's.

Facts

Latestv0.0.8ReleasedLast pushLicenceApache-2.0

Where it sits

Lives in
Provides
Agent access to your codeCAPAgent access to your codecapabilityLetting a coding agent read the project or the system you actually have, reach its model, its objects and its checks, and act on it. In file-based environments that works out of the box; complex systems need dedicated access capabilities. Whatever the environment, the agent also needs project- and framework-specific context, so it understands the thing in front of it rather than guessing from what it remembers of its training data. The transport is incidental: an MCP server, a language server or a CLI answer the same question, and what differs between them is how much of the real thing the agent can see. Distinct from [MCP servers](capability:mcp-servers), which is a protocol adapter on your own running service, and from [agent guidance](capability:agent-guidance), which is knowledge handed over as files rather than read from the thing itself.DocumentationCAPDocumentationcapabilityFinding the answer in what has already been written, and writing it where it has not — first-party documentation made searchable by something other than a person scrolling it, including by an agent, and a document of custom code produced from the code itself.
Requires
@sap/cds@sap/cdsartifactThe CDS runtime version the project's model is compiled with for search_model. When the project provides no local CDS, the @sap/cds runtime version of a globally installed cds-dk is used instead.
Optional
@sap/cds-dk@sap/cds-dkartifactSupplies the @sap/cds runtime version the model is compiled with when the project itself provides none.cds runtime fallback
Designs
Agentic Engineering for SAP BTP ExtensionsAgentic Engineering for SAP BTP Extensionsreference architectureSAP MCP knowledge source

Who is behind it

SAP Cloud Application Programming ModelSAP Cloud Application Programming ModelOrganisationMaintains this
In the atlas: maintains 34
@cap-js
maintainerChristian GeorgiPersonContributes to this
In the atlas: maintains 1, contributes to 53
@chgeo
Dr. David A. KunzPersonContributes to this
In the atlas: contributes to 16
@David-Kunz
Kevin RiedelsheimerPersonContributes to this
In the atlas: contributes to 11
@KevinRiedelsheimer
Simon KoblerPersonContributes to this
In the atlas: contributes to 6
@KoblerS
Lars PlessingPersonContributes to this
In the atlas: contributes to 9
@larsPlessing
Ole LilienthalPersonContributes to this
In the atlas: contributes to 1
@ole-lilienthal
Vladimirs SemikinsPersonContributes to this
In the atlas: contributes to 1
@seVladimirs
sjvansPersonContributes to this
In the atlas: contributes to 45
@sjvans
Mahati ShankarPersonContributes to this
In the atlas: contributes to 4
@smahati
Steffen WaldmannPersonContributes to this
In the atlas: contributes to 25
@swaldmann
10 contributors

Before choosing this

Conditions

PracticalFunctional boundary

The tools are documented as meant for AI models and not a stable API, so anything built to parse cds-mcp output rather than to feed a model can break between releases. Its corpus is the CAP documentation, so Fiori elements, BTP service or ABAP questions are not in what search_docs indexes.

What it declares

Every artifact

Type
MCP server
Origin
By SAP

As an MCP server

Transport
stdio

Connections6

@cap-js/mcp-server connections@cap-js/mcp-serverPROVIDES→ provides2provides stated An MCP server for AI-assisted development of CAP projects, started by the MCP client as `npx -y @cap-js/mcp-server` and also usable as the `cds-mcp` command: search_model fuzzy-matches names of definitions from the compiled CDS model, which includes annotations and HTTP endpoints, and search_docs searches preprocessed CAP documentation stored as embeddings, on the developer's own machine. Retrieval for search_docs combines semantic cosine similarity with BM25 keyword search through weighted reciprocal rank fusion, with optional local cross-encoder reranking. Model access is restricted to the workspace roots the client advertises, and the tools are documented as not a stable API. cap-js/mcp-server — README, About This Project: https://raw.githubusercontent.com/cap-js/mcp-server/main/README.md cap-js/mcp-server — README, Setup: https://raw.githubusercontent.com/cap-js/mcp-server/main/README.md cap-js/mcp-server — README, CLI Usage: https://raw.githubusercontent.com/cap-js/mcp-server/main/README.md cap-js/mcp-server — README, search_model: https://raw.githubusercontent.com/cap-js/mcp-server/main/README.md cap-js/mcp-server — README, search_model on the compiled model: https://raw.githubusercontent.com/cap-js/mcp-server/main/README.md cap-js/mcp-server — README, search_docs: https://raw.githubusercontent.com/cap-js/mcp-server/main/README.md cap-js/mcp-server — README, note on the tools: https://raw.githubusercontent.com/cap-js/mcp-server/main/README.md cap-js/mcp-server — CHANGELOG, 0.0.7 hybrid search: https://raw.githubusercontent.com/cap-js/mcp-server/main/CHANGELOG.md cap-js/mcp-server — CHANGELOG, 0.0.7 reranking: https://raw.githubusercontent.com/cap-js/mcp-server/main/CHANGELOG.md cap-js/mcp-server — CHANGELOG, 0.0.6 workspace roots: https://raw.githubusercontent.com/cap-js/mcp-server/main/CHANGELOG.md Model Context Protocol Adapter | capire: https://cap.cloud.sap/docs/guides/ai/cap-mcpAgent access to your codeprovides stated Makes the CAP documentation searchable by an agent, or from a terminal through `cds-mcp search_docs`: the search_docs tool queries preprocessed CAP documentation stored as embeddings and finds pages whose wording differs from the query, all on the local machine. The embeddings are versioned against capire and resolved through a local manifest, and CDS_MCP_OFFLINE uses the locally cached embeddings without checking for updates. cap-js/mcp-server — README, search_docs: https://raw.githubusercontent.com/cap-js/mcp-server/main/README.md cap-js/mcp-server — README, CLI Usage example: https://raw.githubusercontent.com/cap-js/mcp-server/main/README.md cap-js/mcp-server — README, Environment Variables: https://raw.githubusercontent.com/cap-js/mcp-server/main/README.md cap-js/mcp-server — CHANGELOG, 0.0.6 capire-versioned embeddings: https://raw.githubusercontent.com/cap-js/mcp-server/main/CHANGELOG.mdDocumentationUSED BY← optionally used by1optionally used by derived If: the sap-cap-capire plugin is used in a client that activates the MCP server its .mcp.json registers; in a client that does not, the README says that file is a connection recipe to configure by hand What plugins/sap-cap-capire/.mcp.json registers for that one plugin, pinned to version 0.0.5. Through: inverted from its requires edge secondsky/sap-skills — plugins/sap-cap-capire/.mcp.json: https://raw.githubusercontent.com/secondsky/sap-skills/main/plugins/sap-cap-capire/.mcp.json secondsky/sap-skills — README, portability note: https://github.com/secondsky/sap-skillssecondsky/sap-skillsifNEEDS→ needs1needs stated The CDS runtime version the project's model is compiled with for search_model. When the project provides no local CDS, the @sap/cds runtime version of a globally installed cds-dk is used instead. cap-js/mcp-server — CHANGELOG, 0.0.7: https://raw.githubusercontent.com/cap-js/mcp-server/main/CHANGELOG.md@sap/cds→ optionally needs1optionally needs stated If: the project provides no local CDS Supplies the @sap/cds runtime version the model is compiled with when the project itself provides none. cap-js/mcp-server — CHANGELOG, 0.0.7: https://raw.githubusercontent.com/cap-js/mcp-server/main/CHANGELOG.md@sap/cds-dkifLINEAGE← inspired1inspired derived Through: inverted from its lineage edge@neoimpulse/cap-js-mcp

Install

npm add @cap-js/mcp-server

Derived from the package name. No recipe recorded; the README has the configuration.

Learn more3

Readings
  1. AI Assisted CAP DevelopmentSAP Developers, YouTube — SAP Developers playlists
  2. Boost your CAP Development with AI: Introducing the MCP Server for CAPBirgitS, SAP Community
  3. OData to outcomes—Build AI-enabled SAP Fiori apps using SAP Fiori elementsStefan Engelhardt, SAP TechEd — session catalogue
Where @cap-js/mcp-server runscap-js/mcp-server — README, VS Code mcp.json example, checked 2026-10-18: “"type": "stdio"”stdiodocumentedrequiresdocumentedmay needif the project provides nolocal CDSYour MCP client, actorYour MCP client@cap-js/mcp-server, module@cap-js/mcp-server@sap/cds, module@sap/cds@sap/cds-dk, module@sap/cds-dk
SAPnot SAP's, or the project's ownstated in the documentdocumented onlyunder a condition

README

quoted from cap-js/mcp-server under Apache-2.0, read
cap-js/mcp-server/README.mdOn GitHub

Welcome to @cap-js/mcp-server

REUSE status

About This Project

A Model Context Protocol (MCP) server for the SAP Cloud Application Programming Model (CAP). Use it for AI-assisted development of CAP applications (agentic coding).

The server helps AI models answer questions such as:

  • Which CDS services are in this project, and where are they served?
  • What are the entities about and how do they relate?
  • How do I add columns to a select statement in CAP Node.js?

Table of Contents

Requirements

See Getting Started on how to jumpstart your development and grow as you go with SAP Cloud Application Programming Model.

Setup

Configure your MCP client (Cline, opencode, Claude Code, GitHub Copilot, etc.) to start the server using the command npx -y @cap-js/mcp-server as in the following examples.

Usage in Claude Code

Register the server with Claude Code.

For all projects (user scope):

claude mcp add --scope user cds-mcp -- npx -y @cap-js/mcp-server

For the current project only (local scope, not committed):

claude mcp add cds-mcp -- npx -y @cap-js/mcp-server

For the current project only (committed to the repository):

claude mcp add --scope project cds-mcp -- npx -y @cap-js/mcp-server

To set an environment variable, add --env before the server name:

claude mcp add --scope user --env CDS_MCP_MODEL=nomic-ai/nomic-embed-text-v1.5 cds-mcp -- npx -y @cap-js/mcp-server
Usage in VS Code

Example for VS Code extension Cline:

{
  "mcpServers": {
    "cds-mcp": {
      "command": "npx",
      "args": ["-y", "@cap-js/mcp-server"],
      "env": {}
    }
  }
}

Example for VS Code global mcp.json:

Note: GitHub Copilot uses the mcp.json file as source for it's Agent mode.

{
  "servers": {
    "cds-mcp": {
      "command": "npx",
      "args": ["-y", "@cap-js/mcp-server"],
      "env": {},
      "type": "stdio"
    },
    "inputs": []
  }
}

To set an environment variable, replace the server's empty env object with:

"env": {
  "CDS_MCP_MODEL": "nomic-ai/nomic-embed-text-v1.5"
}

See VS Code Marketplace for more agent extensions.

Usage in OpenAI Codex

Register the server with OpenAI Codex:

codex mcp add cds-mcp -- npx -y @cap-js/mcp-server

To set an environment variable, add --env before the command:

codex mcp add cds-mcp --env CDS_MCP_MODEL=nomic-ai/nomic-embed-text-v1.5 -- npx -y @cap-js/mcp-server
Usage in opencode

Add to opencode.jsonc in your project, or to ~/.config/opencode/opencode.jsonc for global use:

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "cds-mcp": {
      "type": "local",
      "command": ["npx", "-y", "@cap-js/mcp-server"],
      "environment": {
        "CDS_MCP_MODEL": "nomic-ai/nomic-embed-text-v1.5"
      },
      "enabled": true
    }
  }
}

This is the opencode v1 format. In opencode v2, use the same config but nest the server under "servers" — "mcp": { "servers": { "cds-mcp": { ... } } } — or use the CLI instead:

opencode mcp add --global cds-mcp -- npx -y @cap-js/mcp-server

To set an environment variable:

opencode mcp add --global cds-mcp \
  --env CDS_MCP_MODEL=nomic-ai/nomic-embed-text-v1.5 \
  -- npx -y @cap-js/mcp-server
Environment Variables
VariableDescription
CDS_MCP_OFFLINESet to true to use locally cached embeddings without checking for updates. Accepts true or false.
CDS_MCP_MODELNon-empty embedding model name.
CDS_MCP_MANIFEST_TIMEOUTManifest request timeout in positive integer milliseconds. Defaults to 15000.
CDS_MCP_DOWNLOAD_TIMEOUTBundle response-header timeout in positive integer milliseconds. Defaults to 30000.
CDS_MCP_GENERIC_EMBEDDINGSSet to true to skip the runtime filter and search all runtimes. By default search_docs keeps only the chunks of the detected project runtime (Node.js or Java) plus the runtime-agnostic chunks.
CDS_MCP_MAX_RESULTSUpper limit on the number of search_docs results, as a positive integer. Caps the per-call maxResults.
RERANK_ENABLEDSet to true to rerank search_docs results with a local cross-encoder model. Accepts true or false; disabled by default.
CDS_MCP_RERANK_MODELNon-empty cross-encoder model name used when reranking. Defaults to Xenova/ms-marco-MiniLM-L-6-v2.
CDS_MCP_RERANK_DTYPENon-empty data type used to load the reranking model. Defaults to q8; set to fp32 for models without model_quantized.onnx.
CDS_MCP_RERANK_EXTERNAL_DATASet to true for reranking models whose ONNX weights are stored in external .onnx_data files. Accepts true or false.
CDS_MCP_RERANK_BATCH_SIZEPositive integer number of results to process in each reranking batch. Defaults to 1.
Rules

The following rules help the LLM use the server correctly:

- You MUST search for CDS definitions, like entities, fields and services (which include HTTP endpoints) with cds-mcp, only if it fails you MAY read \*.cds files in the project.
- You MUST search for CAP docs with cds-mcp EVERY TIME you create, modify CDS models or when using APIs or the `cds` CLI from CAP. Do NOT propose, suggest or make any changes without first checking it.

Add these rules to your existing global or project-specific AGENTS.md (specifics may vary based on respective MCP client).

CLI Usage

You can also use the tools directly from the command line.

npm i -g @cap-js/mcp-server

Warning

When the package is installed globally, npx uses the installed version instead of downloading the latest from npm. You must update the package manually:

npm update -g @cap-js/mcp-server

This will provide the command cds-mcp, with which you can invoke the tools directly as follows.

# Search CAP documentation
cds-mcp search_docs "how to add columns to a select statement in CAP Node.js" 1

# Search for CDS model definitions
cds-mcp search_model . Books entity

Available Tools

Note

Tools are meant to be used by AI models and do not constitute a stable API.

The server provides these tools for CAP development:

search_docs

This tool uses vector embeddings to locally search through preprocessed CAP documentation, stored as embeddings. The process works as follows:

  1. Query processing: Your search query is converted to an embedding vector.
  2. Similarity search: The system finds documentation chunks with the highest semantic similarity to your query.

This semantic search approach enables you to find relevant documentation even when your query does not use the exact keywords found in the docs, all locally on your machine.

search_model

This tool performs fuzzy searches against names of definitions from the compiled CDS model (Core Schema Notation). CDS compiles all your .cds files into a unified model representation that includes:

  • All definitions and their relationships
  • Annotations
  • HTTP endpoints

The fuzzy search algorithm matches definition names and allows for partial matches, making it easy to find entities like "Books" even when searching for "book".

Support, Feedback, Contributing

This project is open to feature requests/suggestions, bug reports, and so on, via GitHub issues. Contribution and feedback are encouraged and always welcome. For more information about how to contribute, the project structure, as well as additional contribution information, see our Contribution Guidelines.

Security / Disclosure

If you find any bug that may be a security problem, please follow our instructions at in our security policy on how to report it. Please don't create GitHub issues for security-related doubts or problems.

Code of Conduct

We as members, contributors, and leaders pledge to make participation in our community a harassment-free experience for everyone. By participating in this project, you agree to abide by its Code of Conduct at all times.

Licensing

Copyright 2025 SAP SE or an SAP affiliate company and @cap-js/cds-mcp contributors. Please see our LICENSE for copyright and license information. Detailed information including third-party components and their licensing/copyright information is available via the REUSE tool.

Acknowledgments

  • onnxruntime-web is used for creating embeddings locally.
  • @huggingface/transformers.js is used to compare the output of the WordPiece tokenizer.
  • @modelcontextprotocol/sdk provides the SDK for MCP.
Apache-2.0, read

History

Latest

v0.0.8

Features 2, Changed 2, Fixes 1

Notes
Added
  • Accept precomputed canonicalChunks in createEmbeddings, validated as an array at creation time
  • Export the default MODEL constant from calculateEmbeddings
Changed
  • Changed the default embedding model from sentence-transformers/all-MiniLM-L6-v2 to BAAI/bge-small-en-v1.5 for improved retrieval quality
  • Clarified the search_docs tool and query parameter descriptions, guiding term choice toward specific concepts and away from corpus-wide terms
Fixed
  • Bound all network requests with AbortSignal.timeout (manifest 6 s, bundle download 10 s) so hung or slow upstream servers cannot block the server indefinitely
  1. v0.0.7

    Features 3, Changed 1, Fixes 4

    Notes
    Added
    • Hybrid search for search_docs: semantic cosine similarity combined with BM25 keyword search (SQLite FTS5, with a pure-JS fallback when FTS5 is not compiled into node:sqlite) via weighted Reciprocal Rank Fusion
    • Optional local cross-encoder reranking of search_docs results, opt-in via RERANK_ENABLED
    • Fall back to the globally installed cds-dk's @sap/cds runtime version when the project provides no local CDS
    Changed
    • Skip the daily embeddings-bundle re-check when the local files are fresh (within one day), scoped to the detected runtime
    Fixed
    • Fall back to local embeddings when the bundle download fails due to a network error
    • Read the RFC 9457 detail field from non-OK bundle fetch responses for clearer error messages
    • Anchor the ONNX model cache to the package root instead of the caller's working directory
    • Exclude OData-contained entities from the exposed model by computing the contained set from the compiled model (the runtime _containedEntities getter is absent on compiled definitions)
  2. v0.0.6

    Features 3, Changed 4, Fixes 6

    Notes
    Added
    • Configurable embedding model per client via the --model <name> CLI flag and CDS_MCP_MODEL environment variable
    • Capire-versioned embeddings with local manifest resolution
    • Per-chunk metadata in searchMarkdownDocs output
    Changed
    • Changed the default embedding model from Xenova/all-MiniLM-L6-v2 to sentence-transformers/all-MiniLM-L6-v2
    • Switched to CAP AI SQLite VECTOR_EMBEDDING
    • Improved search_docs query param description
    • Replaced background model polling and CDS_MCP_REFRESH_MS with request-driven model and configuration refresh
    Fixed
    • Blank Cache-Control/Pragma so conditional GET can 304, avoiding a full re-download of the embeddings bundle on every startup
    • Isolated project model caches and CAP compiler/global state across requests
    • Preserved transitive model imports for explicitly trusted direct CLI projects
    • Prevented rejected MCP model compilations from exposing out-of-root diagnostics
    • Refreshed cached models after changes to CAP project configuration
    • Restricted MCP model access to advertised workspace roots, including symlink and resolved-source validation
  3. v0.0.5

    Features 1

    Notes
    Added
    • CLI argument management with --offline and --download-embeddings
  4. v0.0.4

    Features 2

    Notes
    Added
    • Support for MCP Bundles (Claude Desktop), Claude Code CLI plugin, and Claude Code MCP config
    • Support for MCP Registry
  5. v0.0.3

    Changed 1

    Notes
    Changed
    • Slightly different rules to search docs when using cds CLI
  6. v0.0.2

    Fixes 1

    Notes
    Fixed
    • Recompilation after compilation of an empty project
  7. v0.0.1

    Features 1

    Notes
    Added
    • Initial release
11,487downloads per week, npm
Weekly downloads for @cap-js/mcp-server26 complete calendar weeks from 2026-04-27 to 2026-10-25; the latest total is 11487.27 Apr – 3 May: 14,2304 May – 10 May: 14,41911 May – 17 May: 13,81518 May – 24 May: 14,85625 May – 31 May: 46,1171 Jun – 7 Jun: 50,3518 Jun – 14 Jun: 55,54515 Jun – 21 Jun: 71,49022 Jun – 28 Jun: 63,52829 Jun – 5 Jul: 67,2636 Jul – 12 Jul: 66,34113 Jul – 19 Jul: 73,09220 Jul – 26 Jul: 70,03027 Jul – 2 Aug: 67,1653 Aug – 9 Aug: 67,84110 Aug – 16 Aug: 50,07117 Aug – 23 Aug: 61,73624 Aug – 30 Aug: 68,08031 Aug – 6 Sept: 50,1757 Sept – 13 Sept: 41,50314 Sept – 20 Sept: 47,16521 Sept – 27 Sept: 59,80628 Sept – 4 Oct: 64,3105 Oct – 11 Oct: 49,38612 Oct – 18 Oct: 33,42919 Oct – 25 Oct: 11,487

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  4. sap-note-search-mcpMCP server searching and fetching SAP Notes and KBAsfrom BTP/BAIP
  5. sap-roadmap-mcpMCP server over SAP Road Map Explorerfrom BTP/BAIP
  6. ui5-lib-diffHosted app listing changes between SAPUI5 or OpenUI5 versionsfrom UI5
  7. abap-docNode.js command writing PDF documentation for an ABAP packagefrom ABAP
  8. sap-ai-docs-mcpMCP server with semantic search over SAP AI Core documentationfrom BTP/BAIP
  9. sap-btp-docs-mcpMCP server with semantic search over SAP BTP documentationfrom BTP/BAIP
  10. @sap-ux/fiori-docs-embeddingsFiori documentation indexed as embeddingsfrom CAP
  11. Clean-Core.ioHosted workspace redrawing custom ABAP as BPMN and grading itfrom ABAP
  12. abapdocs-code-scannerReads the abapDoc comments of a class or interface's public methods and type definitions and returns their text at runtime.from ABAP
  13. @ui5/webcomponents-mcp-serverMCP server answering questions on UI5 Web Componentsfrom UI5
  14. vscode-ui5-api-referenceVS Code side bar view of the SAPUI5 and OpenUI5 API referencefrom UI5

Details

Sources4
npm registrydiscovered herechecked
npm registry, @cap-js/mcp-serverversion, releases, installschecked
github.com/git+https://github.com/cap-js/mcp-server.gittree, pushes, contributors, CIchecked
README.mdquoted, and what the entry declareschecked

Sources are graph entities: the same page may back several entries, and an unreachable source flags every row that rests on it.

Compatibility and provenance
latestv0.0.8
first release
releases and cadence8, ~18d median
discovered vianpm registry
first seen in the atlas
ecosystem and domaincap, ai-and-agents
Contributors10
History in the atlas1
  1. First seen.
For your agent
Ref
artifact:cap-js-mcp-server
JSON
/artifacts/cap-js-mcp-server.json
MCP
Connecting an agent