This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
Professional MCP server for integrating Catalog tasks into the Gemini CLI. Manage data catalogs, collections, and master data using natural language.
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.
Related MCP server: Verodat MCP Server
Node.js (v18+) and npm installed.
Install the extension and its dependencies:
npm run install-deps
npm run build
gemini extensions install .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).
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.
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.
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List datasets, schemas, run APL queries, and use prompts for exploration, anomalies, and monitoring.
Work with your database from AI tools: ask, export, approved changes, and scheduled jobs.
The all-in-one data stack for agents. Upload files, run SQL, evolve tables, and render charts.
Create, read, update and delete your data lake with simple prompts. Share tables by row and column.
