Dataiku DSS MCP Server

A comprehensive Model Context Protocol (MCP) server for Dataiku DSS integration. This project provides Claude Code with direct access to Dataiku DSS for managing recipes, datasets, and scenarios.

🚀 Quick Start

Prerequisites

• Node.js 18.0.0+
• Dataiku DSS instance with API access
• Valid DSS API key

Installation

# Install globally
npm install -g @zhangzichao2008/mcp-dataiku

# Or use with npx
npx @zhangzichao2008/mcp-dataiku

Configuration

1. Copy environment template:

cp .env.sample .env

2. Configure your DSS connection in .env:

DSS_HOST=https://your-dss-instance.com:10000
DSS_API_KEY=your-api-key-here
DSS_INSECURE_TLS=true  # Only if using self-signed certificates

Claude Code Integration

Register the MCP server with Claude Code:

claude mcp add dataiku-dss \
    -e DSS_HOST=https://your-dss-instance.com:10000 \
    -e DSS_API_KEY=your-api-key-here \
    -e DSS_INSECURE_TLS=true \
    -- npx @zhangzichao2008/mcp-dataiku

📚 MCP Tool Catalog

Core Recipe Management Tools

Tool	Description	Key Parameters
create_recipe	Create new recipe	project_key, recipe_type, recipe_name, inputs, outputs, code
update_recipe	Update existing recipe	project_key, recipe_name, **kwargs
delete_recipe	Delete recipe	project_key, recipe_name
run_recipe	Execute recipe	project_key, recipe_name, build_mode

Core Dataset Management Tools

Tool	Description	Key Parameters
create_dataset	Create new dataset	project_key, dataset_name, dataset_type, params
update_dataset	Update dataset settings	project_key, dataset_name, **kwargs
delete_dataset	Delete dataset	project_key, dataset_name, drop_data
build_dataset	Build dataset	project_key, dataset_name, mode, partition
inspect_dataset_schema	Get dataset schema	project_key, dataset_name
check_dataset_metrics	Get dataset metrics	project_key, dataset_name

Core Scenario Management Tools

Tool	Description	Key Parameters
create_scenario	Create new scenario	project_key, scenario_name, scenario_type, definition
update_scenario	Update scenario settings	project_key, scenario_id, **kwargs
delete_scenario	Delete scenario	project_key, scenario_id
run_scenario	Execute scenario	project_key, scenario_id

🔧 Advanced Tools

Tool	Description	Key Parameters
get_scenario_logs	Get detailed run logs and error messages	project_key, scenario_id, run_id
get_recipe_code	Extract actual Python/SQL code from recipes	project_key, recipe_name
get_project_flow	Get complete data flow/pipeline structure	project_key
get_dataset_sample	Get sample data from datasets	project_key, dataset_name, rows, columns
get_recent_runs	Get recent run history across scenarios/recipes	project_key, limit, status_filter
list_projects	List all available Dataiku projects	-

Additional Dataset Tools

Tool	Description	Key Parameters
list_datasets	List all datasets in a project	project_key, dataset_type (optional)
get_dataset_info	Get detailed information about a dataset	project_key, dataset_name
clear_dataset	Clear data from a dataset	project_key, dataset_name, partition (optional)

Additional Recipe Tools

Tool	Description	Key Parameters
list_recipes	List all recipes in a project	project_key, recipe_type (optional)
get_recipe_info	Get detailed information about a recipe	project_key, recipe_name
validate_recipe_syntax	Validate Python/SQL syntax of a recipe	project_key, recipe_name, code (optional)
test_recipe_dry_run	Test recipe logic without actual execution	project_key, recipe_name, sample_rows

Additional Scenario Tools

Tool	Description	Key Parameters
list_scenarios	List all scenarios in a project	project_key, scenario_type, active_only
get_scenario_info	Get detailed information about a scenario	project_key, scenario_id
add_scenario_trigger	Add a trigger to a scenario	project_key, scenario_id, trigger_type, trigger params
remove_scenario_trigger	Remove a trigger from a scenario	project_key, scenario_id, trigger_idx
get_scenario_run_history	Get run history for a scenario	project_key, scenario_id, limit
get_scenario_steps	Get step configuration including Python code	project_key, scenario_id
clone_scenario	Clone an existing scenario with modifications	project_key, source_scenario_id, new_scenario_name, modifications

Advanced Tools

Tool	Description	Key Parameters
search_project_objects	Search for datasets, recipes, scenarios by name/pattern	project_key, search_term, object_types
get_code_environments	List available Python/R environments	project_key (optional)
get_project_variables	Get project-level variables and configuration	project_key
get_connections	List available data connections	project_key (optional)
get_job_details	Get detailed job execution information	project_key, job_id
cancel_running_jobs	Cancel running jobs/scenarios	project_key, job_ids
batch_update_objects	Update multiple objects with similar changes	project_key, object_type, pattern, updates
get_project_flow	Get complete data flow/pipeline structure	project_key
export_project_config	Export project configuration as JSON/YAML	project_key, format
duplicate_project_structure	Copy project structure to new project	source_project_key, target_project_key, include_data

Total: 46 Tools

🔧 Usage Examples

Core Operations

Creating a Python Recipe

{
  "project_key": "ANALYTICS_PROJECT",
  "recipe_type": "python",
  "recipe_name": "data_cleaner",
  "inputs": ["raw_data"],
  "outputs": [{"name": "clean_data", "new": true, "connection": "filesystem_managed"}],
  "code": "import pandas as pd\ndf = dataiku.Dataset(\"raw_data\").get_dataframe()\ndf_clean = df.dropna()\ndataiku.Dataset(\"clean_data\").write_with_schema(df_clean)"
}

Building a Dataset

{
  "project_key": "BI",
  "dataset_name": "user_analytics",
  "mode": "RECURSIVE_BUILD"
}

Getting Dataset Sample

{
  "project_key": "FINANCE_PROJECT",
  "dataset_name": "transactions",
  "rows": 500,
  "columns": ["customer_id", "amount"]
}

Getting Scenario Logs

{
  "project_key": "ANALYTICS_PROJECT",
  "scenario_id": "data_processing"
}

Exploring Project Structure

{
  "project_key": "SALES_ANALYTICS"
}

🏗️ Architecture

mcp-dataiku/
├── src/
│   ├── dataiku-client.ts   # Dataiku API client
│   └── mcp-server.ts       # MCP server implementation
├── package.json
├── tsconfig.json
├── .env.sample
└── README.md

🔒 Security

• API Key Protection: Store API keys in environment variables, never in code
• SSL Configuration: Support for self-signed certificates with DSS_INSECURE_TLS=true
• Permission Validation: All operations respect DSS user permissions
• Error Handling: Sensitive information is not exposed in error messages

📈 Monitoring

The MCP server provides logging for monitoring:

# Check logs for debugging
tail -f dataiku_mcp.log

🤝 Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Commit changes: git commit -m 'Add amazing feature'
4. Push to branch: git push origin feature/amazing-feature
5. Open a Pull Request

Development Setup

# Install dependencies
npm install

# Run in development mode
npm run dev

# Build for production
npm run build

# Run basic validation tests (no actual API calls)
npm test

# Run comprehensive tests (requires Dataiku DSS)
node test-comprehensive.js

# Clean build artifacts
npm run clean

# Publish new version (patch version)
npm run publish:patch

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🔗 Links

• GitHub Repository
• npm Package
• Model Context Protocol
• Claude Code
• Dataiku DSS

📞 Support

If you encounter any issues or have questions, please open an issue on GitHub.

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Ready to enhance your Dataiku workflows with AI assistance! 🚀