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Model Context Protocol (MCP) Integration ​

Integrate HANA CLI with AI coding assistants via the Model Context Protocol for intelligent database operations.

What is MCP? ​

The Model Context Protocol enables AI assistants to interact with external tools and databases. The HANA CLI MCP Server exposes all CLI commands as standardized tools that AI agents can discover and use intelligently.

Key Capabilities:

  • 150+ Tools - All CLI commands accessible via MCP interface
  • Discovery - AI-guided command recommendations and smart search
  • Workflows - Pre-built multi-step task templates
  • Examples - Real-world usage scenarios and parameter presets
  • Documentation - Integrated access to 279 documentation pages
  • Resources - Browsable metadata, schemas, and command catalog
  • Prompts - Guided conversation workflows for common tasks

Quick Start ​

Installation ​

bash
cd mcp-server
npm install
npm run build

Configuration ​

Add to your IDE's MCP settings:

VS Code with Claude Dev or Cline:

json
{
  "mcpServers": {
    "hana-cli": {
      "command": "node",
      "args": [
        "D:/projects/hana-developer-cli-tool-example/mcp-server/build/index.js"
      ],
      "env": {}
    }
  }
}

TIP

Replace the path with your actual project location. Connection credentials are read from default-env.json in the project root. Use hana-cli connect or hana-cli serviceKey to configure database connections.

Core Features ​

1. Command Tools ​

All CLI commands are exposed with the hana_ prefix:

text
hana_status              Check database connection
hana_tables              List tables in a schema
hana_import              Import data from CSV/Excel
hana_dataProfile         Analyze data quality
hana_duplicateDetection  Find duplicate rows
hana_compareSchema       Compare database schemas
hana_inspectTable        View table structure and metadata

Command aliases are also available (e.g., hana_s for status, hana_imp for import).

2. Discovery Tools ​

Help AI agents find the right tools:

hana_recommend - Get command suggestions based on natural language intent:

text
Input: "find duplicate rows in my customer table"
Output: Top 5 matching commands with confidence scores and parameter templates

hana_smart_search - Search across commands, workflows, examples, and presets:

text
Input: "csv import"
Output: Related commands, workflows, examples, and documentation

hana_quickstart - Essential commands guide for new users covering the 6 most common operations.

3. Examples and Presets ​

hana_examples - Get real-world usage scenarios:

text
Input: { command: "import" }
Output: Multiple scenarios with complete parameter sets and best practices

hana_parameter_presets - Pre-configured parameter combinations for common use cases:

text
Input: { command: "dataProfile", useCase: "data_quality" }
Output: Recommended parameters for comprehensive analysis

4. Workflows ​

hana_execute_workflow - Run pre-built multi-step workflows:

text
Available workflows:
- data-quality-check
- schema-comparison
- performance-optimization
- safe-import
- data-migration
... and 15+ more

5. Documentation Access ​

hana_search_docs - Full-text search across all documentation:

text
Input: "import csv with errors"
Output: Top 10 relevant documentation pages with excerpts

hana_get_doc - Retrieve complete documentation page content.

hana_list_doc_categories - Browse documentation by category.

Use Cases ​

Database Exploration ​

Ask your AI assistant:

"Show me the structure of tables in the HR schema"

The AI will:

  1. Use hana_recommend to find relevant commands
  2. Execute hana_tables to list tables
  3. Use hana_inspectTable to examine structure
  4. Format results in a readable summary

Data Quality Analysis ​

"Analyze data quality in my SALES.ORDERS table"

The AI will:

  1. Execute hana_dataProfile for statistical analysis
  2. Run hana_duplicateDetection to find duplicates
  3. Use hana_dataValidator to check constraints
  4. Provide a comprehensive quality report

Import Automation ​

"Import all CSV files from the data/ folder into my schema"

The AI will:

  1. Check available tables with hana_tables
  2. Use hana_examples to get import templates
  3. Generate appropriate import commands for each file
  4. Provide error handling recommendations

Schema Migration ​

"Compare my DEV and PROD schemas and show differences"

The AI will:

  1. Use hana_recommend to find schema comparison tools
  2. Execute hana_compareSchema with both connections
  3. Use result interpretation to highlight key differences
  4. Suggest next steps for migration

Advanced Features ​

Workflow Execution ​

Run complex multi-step workflows:

text
hana_preview_workflow - Preview workflow steps before execution
hana_execute_workflow - Execute complete workflow with automated steps

Result Interpretation ​

hana_interpret_result - AI-friendly analysis and insights from command output, automatically providing context-aware explanations.

Conversation Templates ​

hana_get_conversation_template - Pre-built dialogue flows for guided troubleshooting and task completion.

Connection Management ​

Default Connection ​

The MCP server reads connection details from default-env.json in the project root. Configure using:

bash
# SAP BTP HANA Cloud
hana-cli serviceKey -i instance-name -k key-name

# Interactive setup
hana-cli connect

Project-Specific Connections ​

Tools accept an optional __projectContext parameter:

json
{
  "projectPath": "/path/to/project",
  "connectionFile": "default-env.json"
}

This allows AI agents to work with multiple database connections across different projects.

Complete Documentation ​

For comprehensive guides, implementation details, and troubleshooting:

See Also ​