AI导哈

后端与数据库

neon-ai-gateway

neondatabase/ag…t-skills

One API and one credential for frontier and open-source LLMs and embedding models, built into your Neon branch and powered by Databricks. Use when a user wants to call an LLM, generate embeddings, add AI/chat/an agent to their app, route between model providers (OpenAI, Anthropic, Google/Gemini, Meta, Alibaba, and more), or avoid juggling separate provider API keys and accounts — especially when they already use Neon and want AI requests to branch with their project. Works with the OpenAI SDK, Anthropic SDK, google-genai, the Vercel AI SDK, and Mastra by changing only the base URL. Triggers include "call an LLM", "add AI to my app", "chat completion", "model routing", "LLM proxy/gateway", "one API for all models", "use Claude/GPT/Gemini", "AI SDK", "Mastra agent", "Neon AI Gateway", "generate embeddings", "generate images", and "log/rate-limit AI calls".

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安装命令

npx skills add https://github.com/neondatabase/agent-skills --skill neon-ai-gateway

SKILL.md

FIRST: Use the parent neon skill for a Neon overview, getting started with Neon, Neon development best practices, and more.

If the neon skill is not installed, fetch it from https://neon.com/docs/ai/skills/neon/SKILL.md or install it with:

neon skills -s neon -y

Neon AI Gateway

Currently available in aws-us-east-2, aws-us-east-1, aws-eu-central-1, and aws-ap-southeast-1.

The Neon AI Gateway brings LLM and embedding inference to your Neon branch. One API and one Neon credential give you access to frontier and open-source models from many providers (Anthropic, OpenAI, Google, Meta, and more), plus embedding models, all hosted and powered by Databricks. The catalog shifts over time, so treat /v1/models and the models.dev Neon page as the source of truth rather than a fixed provider list. For embedding model IDs and dimensions, see the embeddings guide. 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 or generate text embeddings and the user would rather not manage model providers themselves:

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