feat: search model via embeddings

CHANGELOG.md

@@ -4,6 +4,12 @@ All notable changes to this project will be documented in this file.
 This project adheres to [Semantic Versioning](http://semver.org/).
 The format is based on [Keep a Changelog](http://keepachangelog.com/).
 
+## Version 0.0.4 - ?
+
+### Changed
+
+- Embeddings-based model search
+
 ## Version 0.0.3 - 2025-09-22
 
 ### Changed

CONTRIBUTING.md

@@ -10,11 +10,11 @@ Instances of abusive, harassing, or otherwise unacceptable behavior may be repor
 
 We use GitHub to manage reviews of pull requests.
 
-* If you are a new contributor, see: [Steps to Contribute](#steps-to-contribute)
+- If you are a new contributor, see: [Steps to Contribute](#steps-to-contribute)
 
-* Before implementing your change, create an issue that describes the problem you would like to solve or the code that should be enhanced. Please note that you are willing to work on that issue.
+- Before implementing your change, create an issue that describes the problem you would like to solve or the code that should be enhanced. Please note that you are willing to work on that issue.
 
-* The team will review the issue and decide whether it should be implemented as a pull request. In that case, they will assign the issue to you. If the team decides against picking up the issue, the team will post a comment with an explanation.
+- The team will review the issue and decide whether it should be implemented as a pull request. In that case, they will assign the issue to you. If the team decides against picking up the issue, the team will post a comment with an explanation.
 
 ## Steps to Contribute
 
@@ -28,11 +28,11 @@ You are welcome to contribute code in order to fix a bug or to implement a new f
 
 The following rule governs code contributions:
 
-* Contributions must be licensed under the [Apache 2.0 License](./LICENSE)
-* Due to legal reasons, contributors will be asked to accept a Developer Certificate of Origin (DCO) when they create the first pull request to this project. This happens in an automated fashion during the submission process. SAP uses [the standard DCO text of the Linux Foundation](https://developercertificate.org/).
+- Contributions must be licensed under the [Apache 2.0 License](./LICENSE)
+- Due to legal reasons, contributors will be asked to accept a Developer Certificate of Origin (DCO) when they create the first pull request to this project. This happens in an automated fashion during the submission process. SAP uses [the standard DCO text of the Linux Foundation](https://developercertificate.org/).
 
 ## Issues and Planning
 
-* We use GitHub issues to track bugs and enhancement requests.
+- We use GitHub issues to track bugs and enhancement requests.
 
-* Please provide as much context as possible when you open an issue. The information you provide must be comprehensive enough to reproduce that issue for the assignee.
+- Please provide as much context as possible when you open an issue. The information you provide must be comprehensive enough to reproduce that issue for the assignee.

README.md

@@ -2,25 +2,20 @@
 
 [![REUSE status](https://api.reuse.software/badge/github.com/cap-js/mcp-server)](https://api.reuse.software/info/github.com/cap-js/mcp-server)
 
-
-
 > [!NOTE]
 > This project is in alpha state.
 
-
-
 ## About This Project
 
 A Model Context Protocol (MCP) server for the [SAP Cloud Application Programming Model (CAP)](https://cap.cloud.sap).
 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](#about-this-project)
@@ -38,14 +33,10 @@ The server helps AI models answer questions such as:
 - [Licensing](#licensing)
 - [Acknowledgments](#acknowledgments)
 
-
-
 ## Requirements
 
 See [Getting Started](https://cap.cloud.sap/docs/get-started) on how to jumpstart your development and grow as you go with SAP Cloud Application Programming Model.
 
-
-
 ## Setup
 
 ```sh
@@ -59,6 +50,7 @@ Configure your MCP client (Cline, opencode, Claude Code, GitHub Copilot, etc.) t
 ### Usage in VS Code
 
 Example for VS Code extension [Cline](https://marketplace.visualstudio.com/items?itemName=saoudrizwan.claude-dev):
+
 ```json
 {
   "mcpServers": {
@@ -91,6 +83,7 @@ See [VS Code Marketplace](https://marketplace.visualstudio.com/search?term=tag%3
 ### Usage in opencode
 
 Example for [opencode](https://github.com/sst/opencode):
+
 ```json
 {
   "mcp": {
@@ -133,50 +126,44 @@ cds-mcp search_docs "how to add columns to a select statement in CAP Node.js" 1
 
 The server provides these tools for CAP development:
 
+### Embeddings Search Technology
+
+Both tools leverage vector embeddings for intelligent search capabilities. This process works as follows:
+
+1. **Query processing:** Your search query is converted to an embedding vector.
+2. **Similarity search:** The system finds content with the highest semantic similarity to your query.
+
+This semantic search approach enables you to find relevant content even when your query does not use the exact keywords, all locally on your machine.
+
 ### `search_model`
 
-This tool performs fuzzy searches against names of definitions from the compiled CDS model (Core Schema Notation).
+This tool searches against definition names 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".
-
 ### `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.
-
+This tool searches through preprocessed CAP documentation from capire with a focus on code snippets, stored as embeddings.
 
 ## Support, Feedback, Contributing
 
 This project is open to feature requests/suggestions, bug reports, and so on, via [GitHub issues](https://github.com/cap-js/mcp-server/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](CONTRIBUTING.md).
 
-
-
 ## Security / Disclosure
 
 If you find any bug that may be a security problem, please follow our instructions at [in our security policy](https://github.com/cap-js/mcp-server/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](https://github.com/cap-js/.github/blob/main/CODE_OF_CONDUCT.md) at all times.
 
-
-
 ## Licensing
 
 Copyright 2025 SAP SE or an SAP affiliate company and @cap-js/cds-mcp contributors. Please see our [LICENSE](LICENSE) for copyright and license information. Detailed information including third-party components and their licensing/copyright information is available [via the REUSE tool](https://api.reuse.software/info/github.com/cap-js/mcp-server).
 
-
-
 ## Acknowledgments
 
 - **onnxruntime-web** is used for creating embeddings locally.