MCP server/database

Datalog Studio MCP Server

Manage data catalogs, collections, and master data using natural language.

★ 1igot-ai/datalog-studio ↗by igot-aiupdated
Manual setup required. The maintainer's config contains paths only you know - edit the placeholders below before adding it to Claude Code.
1

Prepare the server locally

Run this once before adding it to Claude Code.

npm run install-deps
npm run build
gemini extensions install .
2

Register it in Claude Code

claude mcp add -e "DATALOG_API_KEY=${DATALOG_API_KEY}" datalog-studio -- node /path/to/datalog-studio/index.js

Replace any placeholder paths in the command with the real path on your machine.

Required:DATALOG_API_KEY+ 2 optional
3

Make your agent remember this setup

datalog-studio's config, env vars, and the gotchas you hit — recalled in every future Claude Code, Cursor, and Codex session.

npx conare@latest

Free · one command · indexes the sessions already on disk. Set up in the browser instead →

What it does

  • Catalog discovery for workspace data exploration
  • Master data management for collections and attributes
  • Data asset control for listing and analyzing uploaded files
  • Direct data ingestion with automated AI transformation

Tools 5

list_catalogsList all accessible data catalogs.
list_collectionsList collections in a specific catalog.
list_attributesView collection schema and attributes.
list_data_assetsList uploaded files within a collection.
ingest_dataIngest master data into a collection.

Environment Variables

DATALOG_API_KEYrequiredAPI key for authenticating with Datalog Studio.
DATALOG_APICustom domain endpoint for enterprise installations.
CATALOG_URIAPI path suffix for custom enterprise installations.

Try it

List all the data catalogs available in my current workspace.
Show me the collections inside the 'Sales' catalog.
What are the attributes and schema for the 'CustomerData' collection?
List all data assets uploaded to the 'Inventory' collection.
Ingest this new product description into the 'ProductCatalog' collection.
Original README from igot-ai/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 (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.

Frequently Asked Questions

What are the key features of Datalog Studio?

Catalog discovery for workspace data exploration. Master data management for collections and attributes. Data asset control for listing and analyzing uploaded files. Direct data ingestion with automated AI transformation.

What can I use Datalog Studio for?

Quickly querying data schemas without leaving the AI chat interface. Automating the ingestion of unstructured text data into structured collections. Managing and auditing master data assets across enterprise catalogs. Streamlining data discovery for developers and data analysts.

How do I install Datalog Studio?

Install Datalog Studio by running: npm run install-deps && npm run build && gemini extensions install .

What MCP clients work with Datalog Studio?

Datalog Studio works with any MCP-compatible client including Claude Desktop, Claude Code, Cursor, and other editors with MCP support.

Conare · memory for coding agents

Turn this server into reusable context

Keep Datalog Studio docs, env vars, and workflow notes in Conare so your agent carries them across sessions.

Set up free$npx conare@latest