MCP Server Usage & Setup

How to run and use the MCP (Model Context Protocol) server with HANA CLI.

Quick Start

Installation

# Navigate to mcp-server directory
cd mcp-server

# Install dependencies
npm install

# Build TypeScript
npm run build

Running the Server

# Start MCP server (listens on stdio)
node dist/src/index.js

# With debug logging
DEBUG=hana-cli:* node dist/src/index.js

# Specify custom port (for testing)
PORT=3000 node dist/src/index.js

How It Works

The MCP server:

1. Receives tool calls from AI assistants (Claude, etc)
2. Extracts parameters from the request
3. Executes HANA CLI commands in Node.js
4. Returns results in structured markdown format

Available Tools

The MCP server exposes 150+ HANA CLI tools:

Data Tools: import, export, compareData, dataProfile, dataDiff, dataValidator, dataMask, dataSync, duplicateDetection, dataLineage

Schema Tools: compareSchema, schemaClone, tableCopy, erdDiagram, generateDocs, generateTestData

Query Tools: querySimple, callProcedure, tables, views, functions, procedures, roles, etc

System Tools: backup, replicationStatus, partitions, spatialData, and more

Usage with AI Assistants

With Claude Desktop

1. Configure claude_desktop_config.json:

{
  "mcpServers": {
    "hana-cli": {
      "command": "node",
      "args": ["/path/to/mcp-server/dist/src/index.js"],
      "env": {
        "DEBUG": "hana-cli:*"
      }
    }
  }
}

2. Restart Claude Desktop
3. Ask Claude questions about your HANA database

With Custom AI Agents

const { exec } = require('child_process');

// Start MCP server
const server = exec('node mcp-server/dist/src/index.js');

// Send tool call
server.stdin.write(JSON.stringify({
  jsonrpc: "2.0",
  id: 1,
  method: "tools/call",
  params: {
    name: "hana_tables",
    arguments: {
      schema: "MY_SCHEMA",
      __projectContext: {
        projectPath: "/path/to/project"
      }
    }
  }
}));

// Listen for results
server.stdout.on('data', (data) => {
  console.log('MCP Response:', JSON.parse(data));
});

Project Context

When calling MCP tools, pass project context to automatically detect connections:

{
  "schema": "MY_SCHEMA",
  "__projectContext": {
    "projectPath": "/absolute/path/to/project",
    "connectionFile": ".env"
  }
}

The MCP server will:

1. Change to the project directory
2. Look for .env, default-env.json, or connection files
3. Execute the command using the project's database

See Connection Guide for details.

Output Format

All results are returned as markdown tables for easy reading:

| Column1 | Column2 | Column3 |
|---------|---------|---------|
| Value1  | Value2  | Value3  |

Error Handling

When a command fails, the error is returned with:

• Error message
• Command that failed
• Debug information (if available)
• Suggestions for fixes

Example:

Error: Schema MY_SCHEMA not found
Command: hana_tables --schema MY_SCHEMA
Try: Check schema name is correct and you have permissions

Advanced Configuration

Environment Variables

• DEBUG=hana-cli:* - Enable debug logging
• HANA_CLI_PROJECT_PATH - Default project directory
• HANA_CLI_CONN_FILE - Default connection file

Performance Tuning

• Increase node heap: NODE_OPTIONS="--max-old-space-size=4096" node dist/src/index.js
• Use connection pooling for multiple queries
• Batch operations for better performance

Troubleshooting

See MCP Troubleshooting for common issues.

See Also

• Architecture Overview
• Connection Guide
• GitHub MCP Server Code