Datalog Studio MCP Server

Datalog Studio MCP Server

Integrates with the Datalog Studio REST API to explore projects, tables, and assets within a workspace. It enables users to understand data schemas and upload plain text content directly for AI processing.

Category
Visit Server

README

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. You will be prompted for this during installation, or you can set it as an environment variable.

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.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured