原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Cap Js MCP

作者:cap-js版本 0.1.0i★ –i在你的电脑上运行
注册名称io.github.cap-js/mcp-server

安装

概览

作者提供的说明(英文原文)

Model Context Protocol (MCP) server for AI-assisted development of CAP applications.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 其他

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

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

在终端中运行这条命令

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

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

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

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

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

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 cap-js 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32505 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32505 个服务器的 76% 更新
  • 基础检查结果等于或优于此分类中其他 32505 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Cap Js MCP 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.1.0)于11天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, topo^alpin

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211昨天更新
安装

topo^alpin

作者:topoalpin.app

Avalanche bulletins and mountain weather forecasts for any place in the Alps.

在云端运行今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Welcome to @cap-js/mcp-server

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

  • About This Project
  • Requirements
  • Setup
  • Usage in VS Code
  • Usage in Claude Code
  • Usage in OpenAI Codex
  • Usage in opencode
  • CLI Usage
  • Environment Variables
  • Available Tools
  • search_model
  • search_docs
  • Support, Feedback, Contributing
  • Security / Disclosure
  • Code of Conduct
  • Licensing
  • Acknowledgments

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

[!WARNING]

The following environment variables are still experimental.

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.
CDS_MCP_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:

`sh

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.
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