by cap-js
MCP server for AI-assisted development of CAP applications
# Add to your Claude Code skills
git clone https://github.com/cap-js/mcp-serverLast scanned: 7/4/2026
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}mcp-server is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by cap-js. MCP server for AI-assisted development of CAP applications. It has 100 GitHub stars.
mcp-server returned warnings in SkillsLLM's automated security scan. It has no critical vulnerabilities, but review the flagged issues in the Security Report section before adding it to your workflow.
Clone the repository with "git clone https://github.com/cap-js/mcp-server" and add it to your Claude Code skills directory (see the Installation section above).
mcp-server is primarily written in JavaScript. It is open-source under cap-js on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh mcp-server against similar tools.
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Requires a passing catalog security scan. Resolve the flagged issues and resubmit to enable featuring.
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:
See Getting Started on how to jumpstart your development and grow as you go with SAP Cloud Application Programming Model.
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.
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.jsonfile as source for it's Agent mode.
{
"servers": {
"cds-mcp": {
"command": "npx",
"args": ["-y", "@cap-js/mcp-server"],
"env": {},
"type": "stdio"
},
"inputs": []
}
}
See VS Code Marketplace for more agent extensions.
Example for opencode:
{
"mcp": {
"cds-mcp": {
"type": "local",
"command": ["npx", "-y", "@cap-js/mcp-server"],
"enabled": true
}
}
}
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).
You can also use the tools directly from the command line.
npm i -g @cap-js/mcp-server
This will provide the command cds-mcp, with which you can invoke the tools directly as follows.
# Search for CDS model definitions
cds-mcp search_model . Books entity
# Search CAP documentation
cds-mcp search_docs "how to add columns to a select statement in CAP Node.js" 1
[!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_modelThis 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:
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".
search_docsThis tool uses vector embeddings to locally search through preprocessed CAP documentation, stored as embeddings. The process works as follows:
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.
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.
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.
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.
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.