Dataiku DSS Server
БесплатноНе проверенA comprehensive MCP server for Dataiku DSS integration, providing Claude Code with direct access to manage recipes, datasets, and scenarios.
Описание
A comprehensive MCP server for Dataiku DSS integration, providing Claude Code with direct access to manage recipes, datasets, and scenarios.
README
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
- Copy environment template:
cp .env.sample .env
- 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
- Fork the repository
- Create a feature branch:
git checkout -b feature/amazing-feature - Commit changes:
git commit -m 'Add amazing feature' - Push to branch:
git push origin feature/amazing-feature - 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
📞 Support
If you encounter any issues or have questions, please open an issue on GitHub.
Ready to enhance your Dataiku workflows with AI assistance! 🚀
Установить Dataiku DSS Server в Claude Desktop, Claude Code, Cursor
unyly install dataiku-dss-mcp-serverСтавит в Claude Desktop, Claude Code, Cursor и VS Code — сам разбирается с npx, uvx и сборкой из исходников.
Впервые? Поставь CLI: curl -fsSL https://unyly.org/install | sh
Или настроить вручную
Выполни в терминале:
claude mcp add dataiku-dss-mcp-server -- npx -y @zhangzichao2008/mcp-dataikuFAQ
Dataiku DSS Server MCP бесплатный?
Да, Dataiku DSS Server MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Dataiku DSS Server?
Нет, Dataiku DSS Server работает без API-ключей и переменных окружения.
Dataiku DSS Server — hosted или self-hosted?
Доступен hosted-вариант: Unyly запускает сервер в облаке, локальная установка не обязательна.
Как установить Dataiku DSS Server в Claude Desktop, Claude Code или Cursor?
Открой Dataiku DSS Server на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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