A development toolkit that equips AI coding assistants (Claude Code, Cursor, Windsurf) with Databricks platform capabilities, featuring 50+ MCP tools, 19 skill modules, and a Python core library. Supports SQL execution, Jobs management, Unity Catalog, Spark Declarative Pipelines, AI Agent development (Knowledge Assistants, Genie Spaces), and Model Serving.
An open-source, all-in-one platform combining web analytics, session replay, feature flags, and A/B testing for product teams to build successful products.
An open-source AI agent specialized in monitoring PostgreSQL databases, identifying root causes of issues, and providing fix suggestions and performance improvements.
A data analysis tool powered by Claude AI that helps users easily analyze data and generate insights.
An enhanced SQL editor with AI-powered assistance for writing, optimizing, and explaining SQL queries to improve database operation efficiency.
PGMCP is an MCP server that enables querying any PostgreSQL database through natural language. It connects AI assistants to PostgreSQL databases, allowing users to ask questions in plain English and receive structured SQL results with automatic streaming and robust error handling.
EvaDB is a database system designed specifically for AI-powered applications. It provides a powerful SQL API that enables developers to build AI applications with just a few lines of code, supporting both structured and unstructured data processing.
A "code-first" agent framework for seamlessly planning and executing data analytics tasks by interpreting user requests through code snippets and efficiently coordinating various plugins in the form of functions for stateful execution.
An AI-powered open source real-time observability system. Unified metrics and logs collection, centralized alerting distribution, intelligent management and analysis. No Agent required, high performance cluster, provides powerful custom monitoring capabilities.
Vanna is an open-source Python framework that generates accurate SQL queries from natural language questions using Large Language Models (LLMs) and RAG. Version 2.0 introduces enterprise-grade features like user-aware security, row-level permissions, and a pre-built, customizable web UI component that streams tables, charts, and insights in real-time.
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