HANA Cloud MCP Server
@MCP-Mirror
HANA Cloud MCP Server について
Mirror of
基本情報
設定
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"HatriGt_hana-mcp-server": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}ツール
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ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
概要
What is HANA Cloud MCP Server?
The HANA Cloud MCP Server is a Model Context Protocol (MCP) server implementation for SAP HANA Cloud database integration. It provides a standardized interface for managing machine learning models, execution contexts, and communication protocols, and is designed for use with Cursor IDE.
How to use HANA Cloud MCP Server?
Install prerequisites (Python 3.8+, SAP HANA Cloud Database, Flask, HDBCLI, Pandas), then clone the repository, create a virtual environment, install dependencies with pip install -r requirements.txt, and run python setup.py to configure the connection. Configure connection details via environment variables in a .env file (HANA_HOST, HANA_PORT, HANA_USER, HANA_PASSWORD) and start the server.
Key features of HANA Cloud MCP Server
- Model Registry for model metadata and versioning
- Context Management for execution environment configuration
- Protocol Adapters for standardized model-application communication
- Optimized integration with SAP HANA Cloud Database
- Seamless integration with Cursor IDE
Use cases of HANA Cloud MCP Server
- Manage and version machine learning models stored in SAP HANA Cloud
- Configure different execution contexts for deploying models in production or testing
- Enable standardized communication between applications and HANA Cloud models via REST API
- Integrate ML model operations directly within Cursor IDE workflows
FAQ from HANA Cloud MCP Server
What is the architecture of the HANA Cloud MCP Server?
The server uses a three-layer architecture: the Model Layer (for model definitions and metadata), the Context Layer (for execution environments and runtime parameters), and the Protocol Layer (for handling REST API communication between applications and models).
What are the runtime requirements?
Python 3.8+ and an SAP HANA Cloud Database instance are required, along with Flask, HDBCLI (SAP HANA Client for Python), and Pandas as Python dependencies.
Where does the data live?
Data (model metadata, versions, and execution contexts) is stored in the connected SAP HANA Cloud Database, which acts as the persistent backing store.
How is authentication handled?
Authentication to the HANA Cloud database is configured via environment variables (HANA_USER and HANA_PASSWORD) set in a .env file, which the server uses to connect. No additional authentication mechanisms are described.
What transport does the server use?
The server exposes a REST API for client applications to interact with the Model, Context, and Protocol layers. No other transports (e.g., WebSocket, gRPC) are mentioned.
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