Zaturn MCP Server

Zaturn is an MCP server that turns any structured data source into a conversational analytics playground. By exposing SQL execution as a tool, it lets AI assistants answer questions about data without the user writing queries or code. This solves a common pain point for developers and analysts: bridging the gap between raw data and natural‑language insights while keeping the workflow within a single chat interface.

The server acts as a bridge between an AI model and multiple back‑ends. It supports popular relational databases—PostgreSQL, SQLite, DuckDB, MySQL, ClickHouse, SQL Server—and flat files like CSV and Parquet. When a user asks a question, the MCP client translates it into a SQL statement, runs that query on the chosen data source, and returns the result. Because the results can be tabular or textual, developers can quickly prototype dashboards, validate assumptions, or debug data pipelines—all within the chat context.

Beyond raw query results, Zaturn enriches answers with visualizations. It can generate scatter, line, histogram, strip, box, and bar plots directly from query outputs. This visual layer turns raw numbers into immediately interpretable graphics, enabling non‑technical stakeholders to grasp trends without leaving the conversation. The server’s API also supports future extensions such as predictive modeling, forecasting, and automated report generation—features already hinted at in its roadmap.

In practice, Zaturn is ideal for data‑driven teams that rely on AI assistants to surface insights. A product analyst can ask, “What were last quarter’s top‑selling products?” and receive a concise table plus a bar chart. A data engineer can debug schema issues by querying metadata, while a business manager can generate quick presentations from aggregated metrics. Because the tool is MCP‑compatible, it plugs seamlessly into any workflow that already uses AI assistants for code or data tasks.

What sets Zaturn apart is its low friction integration: no SQL learning curve, no separate notebook environment, and instant visual feedback—all powered by a single MCP server. Developers can focus on building higher‑level business logic, confident that the underlying data access and visualization layers are handled automatically by the assistant.