FluentDB
Native macOS database client that lets you query PostgreSQL, MySQL, SQLite, and SQL Server in plain English with built-in safety guardrails.
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Product Overview
What is FluentDB?
FluentDB is a native Mac database client built for Apple Silicon that puts a natural-language layer on top of traditional database management. Instead of memorizing SQL syntax, users can describe what they want in plain English and let the app generate trustworthy queries, while strong guardrails prevent costly mistakes and protect data from leaking. The app also includes a modernized SQL editor, a fast schema explorer, and a data grid capable of handling over 100,000 rows without lag, plus built-in charting and MCP support so external AI agents can manage database connections directly.
Key Features
Bring-Your-Own-Model AI
No proprietary model is baked in; users connect Anthropic, OpenAI, Ollama, or other providers using their own keys, keeping prompts private and outside FluentDB's servers.
Guarded Natural-Language Querying
Ask database questions in everyday English and receive verifiable SQL, with safety guardrails that block destructive or unintended operations before they run.
Modern SQL Editor
A schema-aware editor with autocomplete, auto-formatting, instant results, saved queries, and one-tap switching between manual SQL and AI-assisted mode.
High-Performance Data Grid
Browse and scroll tables with 100,000+ rows in a smooth, stutter-free grid, with a fast ⌘P-driven explorer for jumping between tables and views.
Instant Data Visualization
Convert any query result directly into a chart without leaving the app, speeding up quick data exploration and reporting.
MCP Agent Integration
Expose database connections over the Model Context Protocol so external AI agents can manage and interact with databases programmatically.
Use Cases
- Rapid Database Exploration : Developers can quickly browse unfamiliar schemas and tables across PostgreSQL, MySQL, SQLite, or SQL Server without writing manual queries first.
- AI-Assisted Query Writing : Engineers who aren't SQL experts can describe data requests in English and get accurate, guardrail-checked SQL for everyday reporting tasks.
- Large-Scale Data Review : Teams working with large production tables can inspect and page through massive datasets smoothly, even beyond 100K rows.
- Ad Hoc Data Visualization : Analysts can turn query outputs into charts on the spot for quick internal reviews or presentations, skipping external BI tools.
- Agent-Driven Database Ops : Developers building AI agents can connect them via MCP to automate connection management and routine database maintenance tasks.
FAQs
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