NexQL

AI-native Postgres tooling, All in VS Code

17 followers

AI-native Postgres tooling, All in VS Code

17 followers

NexQL is a PostgreSQL extension for VS Code combining a full database toolkit — tree explorer, SQL notebooks, visual designers, live dashboards. Every suggestion lands in a notebook cell for you to review and run. Production connections default to read-only, with risk scoring and environment tagging. Free AI models included, no API key needed. MCP model for advanced tooling with Copilot / Claude / Antigravity / Cursor / etc. Core is free and MIT-licensed.

Free

Launch tags:Productivity•Developer Tools•Artificial Intelligence

Launch Team / Built With

ClarifyThe autonomous CRM that helps you sell more

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Maker

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AI that's leashed, not autonomous Every AI-generated SQL lands in a notebook cell first — nothing executes without you hitting run. No agent loop that quietly writes to prod. Free, zero-config AI — no API key, no provider account, built-in model behind a managed gateway. Bring-your-own-model too — OpenAI, Anthropic, Gemini, Copilot, or local Ollama/LM Studio. Not locked to one vendor. Safety is structural, not a setting Environment tagging (PROD/STAGING/DEV) with ambient chrome tinting (Sentinel) — you can tell what you're connected to without reading text. Production connections default to read-only; risky writes require explicit confirmation. Query risk scoring with a status bar indicator, before the query runs — not after it fails. Auto-LIMIT + hard 10k row cap prevent accidental full-table scans from freezing the UI. Agentic, and grounded The AI can autonomously look up your live schema, run EXPLAIN, trace FK join paths, and check index health — multi-turn tool calling, not single-shot prompting. Built-in MCP server exposes the same read-only toolset to external agents (Copilot, Claude Desktop, Cursor) — with schema-grounding instructions injected so agents don't hallucinate table names. Notebook-first, not query-window-first .pgsql notebooks persist state across cells — you build a working session, not a disposable scratch pad. Inline results, charts, and exports live next to the query that produced them. Depth most competitors skip entirely Visual, AI-assisted Row-Level Security Policy Studio. Migration Hub auto-detects Prisma, Drizzle, Alembic, Flyway, Atlas, Knex, Rails, golang-migrate in your workspace. Table Intelligence — profile, activity monitor, index usage, bloat detection — not just a schema browser. Native, and actually free Lives inside VS Code — no separate app, no context switch. Core is MIT-licensed and never feature-gated; paid tiers lift daily caps, they don't unlock safety or AI.

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2mo ago

The tree explorer plus the auto-notebook idea feels really natural, like I'm tinkering instead of fighting my editor. Read-only defaults for prod connections is a genuinely thoughtful touch more tools should copy.

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1mo ago

Maker

@beachcoder Thanks for your feedback. Would love to hear suggestions from you on your use-cases and how the product be more helpful for daily use.

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1mo ago

Pazi

An AI-native Postgres toolkit right inside VS Code sounds fantastic — love that suggestions land in a notebook cell to review before running, and read-only defaults for prod. Congrats on the launch!

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1mo ago

Maker

@zvonimir_sabljic1 Appreciate your support

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1mo ago

Pazi

Congrats on the launch! NexQL looks super useful — bringing a full Postgres toolkit right into VS Code is a great idea. Wishing you a strong launch day!

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1mo ago

Forum Threads

p/nexql

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2mo ago

What's missing from your current VS Code PostgreSQL workflow?

We re gearing up to launch NexQL an AI-native PostgreSQL extension built entirely inside VS Code to replace bloated standalone clients and fragmented extensions. We've integrated everything from a fluid tree explorer and interactive SQL notebooks to visual schema designers and live dashboard monitoring directly into your editor.

But here's the thing: we don't want to build this in a vacuum. We want to build it for your daily engineering workflows.

Whether you are optimizing massive multi-tenant data pipelines, tuning query performance, or just trying to quickly visualize a schema layout, we want to know what hurts the most about your current local or cloud database setup.

We d love to hear your thoughts on:

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