Overview
What is HANA Cloud MCP Server?
A Model Context Protocol (MCP) server implementation for SAP HANA Cloud DB integration with Cursor IDE. It provides a standardized interface for managing ML models, execution contexts, and communication protocols between applications and the HANA Cloud database.
How to use HANA Cloud MCP Server?
Clone the repository, create a virtual environment, install dependencies with pip install -r requirements.txt, then run python setup.py and follow the prompts to configure your HANA Cloud connection and server settings. Configuration is managed via environment variables set in a .env file.
Key features of HANA Cloud MCP Server
- Model Registry: Central repository for model metadata and versioning
- Context Management: Configure execution environments for models
- Protocol Adapters: Standardized communication between models and applications
- HANA Cloud Integration: Optimized for SAP HANA Cloud Database
- Cursor IDE Support: Seamless integration with Cursor IDE
Use cases of HANA Cloud MCP Server
- Manage and version machine learning models in SAP HANA Cloud
- Configure and deploy model execution contexts for different environments
- Enable standardized communication between AI applications and HANA Cloud
- Integrate MCP-capable IDEs like Cursor with HANA Cloud DB for ML workflows
FAQ from HANA Cloud MCP Server
What are the prerequisites for HANA Cloud MCP Server?
Python 3.8+, an SAP HANA Cloud Database, and the following Python packages: Flask, HDBCLI (SAP HANA Client for Python), and Pandas.
How do I configure the server’s connection to HANA Cloud?
Set the environment variables HANA_HOST, HANA_PORT, HANA_USER, and HANA_PASSWORD in a .env file.
What is the three-layer architecture of HANA Cloud MCP Server?
The server has a Model Layer (manages model definitions, versions, and metadata), a Context Layer (configures execution environments and runtime parameters), and a Protocol Layer (handles communication between applications and models).
Does HANA Cloud MCP Server require a specific runtime?
Yes, Python 3.8+ is required, and the server runs on Flask.
Where does the server store model data and configurations?
Model metadata, versions, execution contexts, and communication protocols are managed internally and stored via the HANA Cloud DB integration.
