datalog-studio

# Catalog MCP Extension 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](https://nodejs.org) (v18+) and npm installed. ### 2. Installation Install the extension and its dependencies: ```bash 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.