Agent skill · software engineering · sickn33
neon-ai-gateway
One API and one credential for frontier and open-source LLMs, built into your Neon branch and powered by Databricks.
Why this skill is useful
Adds a unified API for multiple LLM providers, enabling seamless model switching and integration without extensive rewiring.
What it needs
Requires neon installed locally. Requires databricks account access. About 8k tokens when loaded. Last updated 2026-08-07. 44,571 stars on the source repository.
What this skill does
Neon AI Gateway This is a preview feature and only available in us-east-2. The Neon AI Gateway is the LLM inference layer built into your Neon branch: one API and one Neon credential give you access to frontier and open-source models from Anthropic, OpenAI, Google, Meta, Alibaba, DeepSeek, and Databricks — powered by Databricks. Your existing OpenAI/Anthropic/Gemini SDK works by changing only the base URL. Use this skill to help the user send model calls through the gateway, wire it into the AI SDK or Mastra, and switch providers without rewiring code. Deliver a working inference request, a configured agent, or a precise answer from the official Neon docs. When to Use Reach for the AI Gateway whenever an app or agent needs to call an LLM and the user would rather not manage model providers themselves: One credential instead of many provider accounts. A single Neon credential reaches the entire model catalog across seven providers. No separate OpenAI / Anthropic / Google billing, keys, or signups to provision and rotate. Switch models without rewiring. The unified endpoint is OpenAI-compatible and works with every model in the catalog — change one model field to move between Claude, GPT, and Gemini. Standard SDKs (OpenAI, Anthropic, google-genai) work with just a base-URL change. AI follows your branches. Each branch has its own gateway endpoint, scoped with the same lineage as your database. AI requests from a preview/feature branch are isolated to that branch — the same isolation your data already gets — which makes preview, CI, and agent environments self-contained. No extra infrastructure, and it's already next to your data. The gateway lives inside your Neon project (and is injected into Neon Functions automatically), runs on the same Databricks infrastructure that serves trillions of tokens a month, and supports streaming (SSE) out of the box. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills sickn33/neon-ai-gateway--849f58