Datalog Studio Server

Professional MCP server for integrating Catalog tasks into the Gemini CLI. Manage data catalogs, collections, and master data using natural language.

Features

• Catalog Discovery: List and find data catalogs within your workspace.
• Master Data Management: Explore collections, attributes, and AI prompt templates.
• Data Asset Control: List uploaded documents and analyze data structures.
• Data Ingestion: Direct data ingestion with automated AI transformation.

Quick Start

1. Prerequisites

• Node.js (v18+) and npm installed.

2. Installation

Install the extension and its dependencies:

npm run install-deps
npm run build
gemini extensions install .

3. Configuration

The extension requires a DATALOG_API_KEY. By default, it connects to https://studio.igot.ai/v1/catalog.

For custom enterprise installations, you can configure the endpoint using:

• DATALOG_API: The domain endpoint (e.g., https://enterprise.com).
• CATALOG_URI: The API path suffix (e.g., /v1/catalog).

Development

Use the provided scripts for a professional development workflow:

• npm run dev: Start MCP server in watch mode.
• npm run lint: Run ESLint to find and fix issues.
• npm run format: Format code with Prettier.
• npm run typecheck: Run TypeScript type checking.
• npm run preflight: Run a full cleanup, install, lint, and build cycle.

Tools Summary

• list_catalogs(): List all accessible data catalogs.
• list_collections(catalog_id): List collections in a specific catalog.
• list_attributes(catalog_name, collection_name): View collection schema and attributes.
• list_data_assets(catalog_name, collection_name): List uploaded files within a collection.
• ingest_data(catalog_name, collection_name, text, transform?): Ingest master data into a collection.